Data scientist jobs in Bossier City, LA

W2 Contract Dallas, TX (Onsite) We are seeking an experienced Data Scientist to join our team in Dallas, Texas. The ideal candidate will have a strong foundation in machine learning, data modeling, and statistical analysis, with the ability to transform complex datasets into clear, actionable insights that drive business impact. Key Responsibilities Develop, implement, and optimize machine learning models to support business objectives. Perform exploratory data analysis, feature engineering, and predictive modeling. Translate analytical findings into meaningful recommendations for technical and non-technical stakeholders. Collaborate with cross-functional teams to identify data-driven opportunities and improve decision-making. Build scalable data pipelines and maintain robust analytical workflows. Communicate insights through reports, dashboards, and data visualizations. Qualifications Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field. Proven experience working with machine learning algorithms and statistical modeling techniques. Proficiency in Python or R, along with hands-on experience using libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow. Strong SQL skills and familiarity with relational or NoSQL databases. Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib). Excellent problem-solving, communication, and collaboration skills.

Role: Applied Data Scientist/ Data Science Engineer Yrs. of experience: 8+ Yrs. Job type : Fulltime Job Responsibilities: You will be part of a team that innovates and collaborates with internal stakeholders to deliver world-class solutions with a customer first mentality. This group is passionate about the data science field and is motivated to find opportunity in, and develop solutions for, evolving challenges. You will: Solve business and customer issues utilizing AI/ML - Mandatory Build prototypes and scalable AI/ML solutions that will be integrated into software products Collaborate with software engineers, business stakeholders and product owners in an Agile environment Have complete ownership of model outcomes and drive continuous improvement Essential Requirements: Strong coding skills in Python and SQL - Mandatory Machine Learning knowledge (Deep learning, Information Retrieval (RAG), GenAI , Classification, Forecasting, Regression, etc. on large datasets) with experience in ML model deployment Ability to work with internal stakeholders to transfer business questions into quantitative problem statements Ability to effectively communicate data science progress to non-technical internal stakeholders Ability to lead a team of data scientists is a plus Experience with Big Data technologies and/or software development is a plus

Senior Data Governance Consultant (Informatica) About Paradigm - Intelligence Amplified Paradigm is a strategic consulting firm that turns vision into tangible results. For over 30 years, we've helped Fortune 500 and high-growth organizations accelerate business outcomes across data, cloud, and AI. From strategy through execution, we empower clients to make smarter decisions, move faster, and maximize return on their technology investments. What sets us apart isn't just what we do, it's how we do it. Driven by a clear mission and values rooted in integrity, excellence, and collaboration, we deliver work that creates lasting impact. At Paradigm, your ideas are heard, your growth is prioritized, your contributions make a difference. Summary: We are seeking a Senior Data Governance Consultant to lead and enhance data governance capabilities across a financial services organization The Senior Data Governance Consultant will collaborate closely with business, risk, compliance, technology, and data management teams to define data standards, strengthen data controls, and drive a culture of data accountability and stewardship The ideal candidate will have deep experience in developing and implementing data governance frameworks, data policies, and control mechanisms that ensure compliance, consistency, and trust in enterprise data assets Hands-on experience with Informatica, including Master Data Management (MDM) or Informatica Data Management Cloud (IDMC), is preferred This position is Remote, with occasional travel to Plano, TX Responsibilities: Data Governance Frameworks: Design, implement, and enhance data governance frameworks aligned with regulatory expectations (e.g., BCBS 239, GDPR, CCPA, DORA) and internal control standards Policy & Standards Development: Develop, maintain, and operationalize data policies, standards, and procedures that govern data quality, metadata management, data lineage, and data ownership Control Design & Implementation: Define and embed data control frameworks across data lifecycle processes to ensure data integrity, accuracy, completeness, and timeliness Risk & Compliance Alignment: Work with risk and compliance teams to identify data-related risks and ensure appropriate mitigation and monitoring controls are in place Stakeholder Engagement: Partner with data owners, stewards, and business leaders to promote governance practices and drive adoption of governance tools and processes Data Quality Management: Define and monitor data quality metrics and KPIs, establishing escalation and remediation procedures for data quality issues Metadata & Lineage: Support metadata and data lineage initiatives to increase transparency and enable traceability across systems and processes Reporting & Governance Committees: Prepare materials and reporting for data governance forums, risk committees, and senior management updates Change Management & Training: Develop communication and training materials to embed governance culture and ensure consistent understanding across the organization Required Qualifications: 7+ years of experience in data governance, data management, or data risk roles within financial services (banking, insurance, or asset management preferred) Strong knowledge of data policy development, data standards, and control frameworks Proven experience aligning data governance initiatives with regulatory and compliance requirements Familiarity with Informatica data governance and metadata tools Excellent communication skills with the ability to influence senior stakeholders and translate technical concepts into business language Deep understanding of data management principles (DAMA-DMBOK, DCAM, or equivalent frameworks) Bachelor's or Master's Degree in Information Management, Data Science, Computer Science, Business, or related field Preferred Qualifications: Hands-on experience with Informatica, including Master Data Management (MDM) or Informatica Data Management Cloud (IDMC), is preferred Experience with data risk management or data control testing Knowledge of financial regulatory frameworks (e.g., Basel, MiFID II, Solvency II, BCBS 239) Certifications, such as Informatica, CDMP, or DCAM Background in consulting or large-scale data transformation programs Key Competencies: Strategic and analytical thinking Strong governance and control mindset Excellent stakeholder and relationship management Ability to drive organizational change and embed governance culture Attention to detail with a pragmatic approach Why Join Paradigm At Paradigm, integrity drives innovation. You'll collaborate with curious, dedicated teammates, solving complex problems and unlocking immense data value for leading organizations. If you seek a place where your voice is heard, growth is supported, and your work creates lasting business value, you belong at Paradigm. Learn more at ******************** Policy Disclosure: Paradigm maintains a strict drug-free workplace policy. All offers of employment are contingent upon successfully passing a standard 5-panel drug screen. Please note that a positive test result for any prohibited substance, including marijuana, will result in disqualification from employment, regardless of state laws permitting its use. This policy applies consistently across all positions and locations.

Technology Recovery Services provides subject matter expertise and direction on complex IT disaster recovery projects/initiatives and supports IT disaster recovery technical planning, coordination and service maturity working across IT, business resilience, risk management, regulatory and compliance. Summary of Essential Functions: Govern disaster recovery plans and procedures for critical business applications and infrastructure. Create, update, and publish disaster recovery related policies, procedures, and guidelines. Ensure annual updates and validations of DR policies and procedures to maintain readiness and resilience. Maintain upto-date knowledge of disaster recovery and business continuity best practices. Perform regular disaster recovery testing, including simulation exercises, incident response simulations, tabletop exercises, and actual failover drills to validate procedures and identify improvements. Train staff and educate employees on disaster recovery processes, their roles during incidents, and adherence to disaster recovery policies. Coordinates Technology Response to Natural Disasters and Aircraft Accidents Qualifications: Strong knowledge of Air vault and ransomware recovery technologies Proven ability to build, cultivate, and promote strong relationships with internal customers at all levels of the organization, as well as with Technology counterparts, business partners, and external groups Proficiency in handling operational issues effectively and understanding escalation, communication, and crisis management Demonstrated call control and situation management skills under fast paced, highly dynamic situations Knowledge of basic IT and Airline Ecosystems Understand SLA's, engagement process and urgency needed to engage teams during critical situations Ability to understand and explain interconnected application functionality in a complex environment and share knowledge with peers Skilled in a Customer centric attitude and the ability to focus on providing best-in-class service for customers and stakeholders Ability to execute with a high level of operational urgency with an ability to maintain calm, and work closely with a team and stakeholders during a critical situation while using project management skills Ability to present to C Level executives with outstanding communication skills Ability to lead a large group up to 200 people including support, development, leaders and executives on a single call Ability to effectively triage - be able to detect and determine symptom vs cause and capture key data from various sources, systems and people Knowledge of business strategies and priorities Excellent communication and stakeholder engagement skills. Required: 3 plus years of similar or related experience in such fields as Disaster Recovery, Business Continuity and Enterprise Operational Resilience. Working knowledge of Disaster Recovery professional practices, including Business Impact Analysis, disaster recovery plan (DRP), redundancy and failover mechanisms DR related regulatory requirement, and Business Continuity Plan exercises and audits. Ability to motivate, influence, and train others. Strong analytical skills and problem-solving skills using data analysis tools including Alteryx and Tableau. Ability to communicate technical and operational issues clearly to both technical and nontechnical audiences.

We are looking for a talented and motivated Python Data Engineers. We need help expanding our data assets in support of our analytical capabilities in a full-time role. This role will have the opportunity to interface directly with our traders, analysts, researchers and data scientists to drive out requirements and deliver a wide range of data related needs. What you will do: - Translate business requirements into technical deliveries. Drive out requirements for data ingestion and access - Maintain the cleanliness of our Python codebase, while adhering to existing designs and coding conventions as much as possible - Contribute to our developer tools and Python ETL toolkit, including standardization and consolidation of core functionality - Efficiently coordinate with the rest of our team in different locations Qualifications - 6+ years of enterprise-level coding experience with Python - Computer Science, MIS or related degree - Familiarity with Pandas and NumPy packages - Experience with Data Engineering and building data pipelines - Experience scraping websites with Requests, Beautiful Soup, Selenium, etc. - Strong understating of object-oriented design, design patterns, SOA architectures - Proficient understanding of peer-reviewing, code versioning, and bug/issue tracking tools. - Strong communication skills - Familiarity with containerization solutions like Docker and Kubernetes is a plus

We are looking for a seasoned Azure Data Engineer to design, build, and optimize secure, scalable, and high-performance data solutions within the Microsoft Azure ecosystem. This will be a multi-year contract worked FULLY ONSITE in Austin, TX. The ideal candidate brings deep technical expertise in data architecture, ETL/ELT engineering, data integration, and governance, along with hands-on experience in MDM, API Management, Lakehouse architectures, and data mesh or data hub frameworks. This position combines strategic architectural planning with practical, hands-on implementation, empowering cross-functional teams to leverage data as a key organizational asset. Key Responsibilities 1. Data Architecture & Strategy Design and deploy end-to-end Azure data platforms using Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure SQL Database. Build and implement Lakehouse and medallion (Bronze/Silver/Gold) architectures for scalable and modular data processing. Define and support data mesh and data hub patterns to promote domain-driven design and federated governance. Establish standards for conceptual, logical, and physical data modeling across data warehouse and data lake environments. 2. Data Integration & Pipeline Development Develop and maintain ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, and Databricks for both batch and streaming workloads. Integrate diverse data sources (on-prem, cloud, SaaS, APIs) into a unified Azure data environment. Optimize pipelines for cost-effectiveness, performance, and scalability. 3. Master Data Management (MDM) & Data Governance Implement MDM solutions using Azure-native or third-party platforms (e.g., Profisee, Informatica, Semarchy). Define and manage data governance, metadata, and data quality frameworks. Partner with business teams to align data standards and maintain data integrity across domains. 4. API Management & Integration Build and manage APIs for data access, transformation, and system integration using Azure API Management and Logic Apps. Design secure, reliable data services for internal and external consumers. Automate workflows and system integrations using Azure Functions, Logic Apps, and Power Automate. 5. Database & Platform Administration Perform core DBA tasks, including performance tuning, query optimization, indexing, and backup/recovery for Azure SQL and Synapse. Monitor and optimize cost, performance, and scalability across Azure data services. Implement CI/CD and Infrastructure-as-Code (IaC) solutions using Azure DevOps, Terraform, or Bicep. 6. Collaboration & Leadership Work closely with data scientists, analysts, business stakeholders, and application teams to deliver high-value data solutions. Mentor junior engineers and define best practices for coding, data modeling, and solution design. Contribute to enterprise-wide data strategy and roadmap development. Required Qualifications Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related fields. 5+ years of hands-on experience in Azure-based data engineering and architecture. Strong proficiency with the following: Azure Data Factory, Azure Synapse, Azure Databricks, Azure Data Lake Storage Gen2 SQL, Python, PySpark, PowerShell Azure API Management and Logic Apps Solid understanding of data modeling approaches (3NF, dimensional modeling, Data Vault, star/snowflake schemas). Proven experience with Lakehouse/medallion architectures and data mesh/data hub designs. Familiarity with MDM concepts, data governance frameworks, and metadata management. Experience with automation, data-focused CI/CD, and IaC. Thorough understanding of Azure security, RBAC, Key Vault, and core networking principles. What We Offer Competitive compensation and benefits package Luna Data Solutions, Inc. (LDS) provides equal employment opportunities to all employees. All applicants will be considered for employment. LDS prohibits discrimination and harassment of any type regarding age, race, color, religion, sexual orientation, gender identity, sex, national origin, genetics, protected veteran status, and/or disability status.

KPI Partners is a 5 times Gartner-recognized data, analytics, and AI consulting company. We are leaders in data engineering on Azure, AWS, Google, Snowflake, and Databricks. Founded in 2006, KPI has over 400 consultants and has successfully delivered over 1,000 projects to our clients. We are looking for skilled data engineers who want to work with the best team in data engineering. Title: Senior Data Architect Location: Plano, TX (Hybrid) Job Type: Contract - 6 Months Key Skills: SQL, PySpark, Databricks, and Azure Cloud Key Note: Looking for a Data Architect who is Hands-on with SQL, PySpark, Databricks, and Azure Cloud. About the Role: We are seeking a highly skilled and experienced Senior Data Architect to join our dynamic team at KPI, working on challenging and multi-year data transformation projects. This is an excellent opportunity for a talented data engineer to play a key role in building innovative data solutions using Azure Native Services and related technologies. If you are passionate about working with large-scale data systems and enjoy solving complex engineering problems, this role is for you. Key Responsibilities: Data Engineering: Design, development, and implementation of data pipelines and solutions using PySpark, SQL, and related technologies. Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into robust data solutions. Data Warehousing: Design and implement data warehousing solutions, ensuring scalability, performance, and reliability. Continuous Learning: Stay up to date with modern technologies and trends in data engineering and apply them to improve our data platform. Mentorship: Provide guidance and mentorship to junior data engineers, ensuring best practices in coding, design, and development. Must-Have Skills & Qualifications: Minimum 12+ years of overall experience in IT Industry. 4+ years of experience in data engineering, with a strong background in building large-scale data solutions. 4+ years of hands-on experience developing and implementing data pipelines using Azure stack experience (Azure, ADF, Databricks, Functions) Proven expertise in SQL for querying, manipulating, and analyzing large datasets. Strong knowledge of ETL processes and data warehousing fundamentals. Self-motivated and independent, with a “let's get this done” mindset and the ability to thrive in a fast-paced and dynamic environment. Good-to-Have Skills: Databricks Certification is a plus. Data Modeling, Azure Architect Certification.

Our client is seeking a Senior Data Analytics Engineer (Customer Data) to join their team! This position is located in remote. Build, optimize, and maintain customer data pipelines in PySpark/Databricks to support CDP-driven use cases across AWS/Azure/GCP Transform raw and integrated customer data into analytics-ready datasets used for dashboards, reporting, segmentation, personalization, and downstream AI/ML applications Develop and enrich customer behavior metrics, campaign analytics, and performance insights such as: ad engagement, lifecycle metrics, retention Partner with Marketing, Sales, Product, and Data Science teams to translate business goals into metrics, features, and analytical data models Build datasets consumed by Power BI/Tableau dashboards (hands-on dashboard creation not required) Ensure high cluster performance and pipeline optimization in Databricks, including troubleshooting skewed joins, sorting, partitioning, and real-time processing needs Work across multiple cloud and vendor ecosystems such as: AWS/Azure/GCP; Hightouch or comparable CDP vendors Participate in the data ingestion and digestion phases, shaping integrated data into analytical layers for MarTech and BI Contribute to and enforce data engineering standards, documentation, governance, and best practices across the organization Desired Skills/Experience: 6+ years of experience in Data Engineering, Analytics Engineering, or related fields, including data modeling experience Strong Data Engineering fundamentals with the ability to design pipelines, optimize performance, and deliver real-time or near-real-time datasets Ability to deeply understand data, identifying gaps, designing meaningful transformations, and creating metrics with clear business context Understanding of how customer data moves through Customer Data Platforms (CDPs) and how to design pipelines that integrate with them Experience supporting Marketing, Customer Data, MarTech, CDP, segmentation, or personalization teams strongly preferred Hands-on experience required with: Databricks, PySpark, Python, SQL, Building analytics datasets for dashboards/reporting and customer behavior analytics or campaign performance insights Experience designing and implementing features that feed downstream AI or customer-facing applications Benefits: Medical, Dental, & Vision Insurance Plans Employee-Owned Profit Sharing (ESOP) 401K offered The approximate pay range for this position starting at $150-160,000+. Please note that the pay range provided is a good faith estimate. Final compensation may vary based on factors including but not limited to background, knowledge, skills, and location. We comply with local wage minimums.

About the Role We are seeking a highly skilled Databricks Data Engineer with strong expertise in modern data engineering, Azure cloud technologies, and Lakehouse architectures. This role is ideal for someone who thrives in dynamic environments, enjoys solving complex data challenges, and can lead end-to-end delivery of scalable data solutions. What We're Looking For 8+ years designing and delivering scalable data pipelines in modern data platforms Deep experience in data engineering, data warehousing, and enterprise-grade solution delivery Ability to lead cross-functional initiatives in matrixed teams Advanced skills in SQL, Python, and ETL/ELT development, including performance tuning Hands-on experience with Azure, Snowflake, and Databricks, including system integrations Key Responsibilities Design, build, and optimize large-scale data pipelines on the Databricks Lakehouse platform Modernize and enhance cloud-based data ecosystems on Azure, contributing to architecture, modeling, security, and CI/CD Use Apache Airflow and similar tools for workflow automation and orchestration Work with financial or regulated datasets while ensuring strong compliance and governance Drive best practices in data quality, lineage, cataloging, and metadata management Primary Technical Skills Develop and optimize ETL/ELT pipelines using Python, PySpark, Spark SQL, and Databricks Notebooks Design efficient Delta Lake models for reliability and performance Implement and manage Unity Catalog for governance, RBAC, lineage, and secure data sharing Build reusable frameworks using Databricks Workflows, Repos, and Delta Live Tables Create scalable ingestion pipelines for APIs, databases, files, streaming sources, and MDM systems Automate ingestion and workflows using Python and REST APIs Support downstream analytics for BI, data science, and application workloads Write optimized SQL/T-SQL queries, stored procedures, and curated datasets Automate DevOps workflows, testing pipelines, and workspace configurations Additional Skills Azure: Data Factory, Data Lake, Key Vault, Logic Apps, Functions CI/CD: Azure DevOps Orchestration: Apache Airflow (plus) Streaming: Delta Live Tables MDM: Profisee (nice-to-have) Databases: SQL Server, Cosmos DB Soft Skills Strong analytical and problem-solving mindset Excellent communication and cross-team collaboration Detail-oriented with a high sense of ownership and accountability

SeAH Superalloy Technologies is building a world-class manufacturing facility in Temple, Texas, producing aerospace-grade nickel-based superalloys for investment casting and additive manufacturing. As part of SeAH Group's $150M U.S. greenfield investment, we're shaping the future of advanced manufacturing and establishing strong partnerships with industry leaders, suppliers, and communities. Position Summary We are seeking a highly skilled and proactive Data Engineer to lead and support the development and optimization of our analytics infrastructure. This role will focus on building scalable, secure, and maintainable data pipelines across enterprise systems like ERP, MES, SCADA, and WMS. The ideal candidate has a strong technical foundation in data engineering, exceptional problem-solving skills, and experience in both on-prem and cloud environments. This role will also involve the development of dashboards, visualization tools, and predictive analytics for use across operations, engineering, and executive leadership. Key Responsibilities Data Engineering & Pipeline Development: Design, build, and maintain robust, fault-tolerant data pipelines and ingestion workflows. Lead integration of key enterprise systems (ERP, MES, CMMS, SCADA, WMS). Optimize pipelines for performance, scalability, and long-term maintainability. Clean, transform, and augment raw industrial data to ensure accuracy and analytical value. System Integration & API Management: Develop and maintain RESTful API connectivity for cross-platform communication. Work with structured and semi-structured data formats (SQL, CSV, PLC logs, etc.). Translate complex business requirements into scalable data architecture. Visualization & Reporting: Create and maintain dashboards and reports using Power BI or similar tools. Automate report generation for predictive analytics, anomaly detection, and performance insights. Collaborate with stakeholders to customize visual outputs and provide decision-ready insights. Data Collection, Governance & Security: Implement ETL processes and ensure proper data governance protocols. Conduct quality checks, monitor ingestion workflows, and enforce secure data handling practices. Perform backups and manage version control for code and reports. Collaboration & Agile Operations: Participate in agile team meetings, code reviews, and sprint planning. Support internal teams with technical troubleshooting and training. Gather requirements directly from stakeholders to refine data strategies. Qualifications Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. 5+ years of professional experience in data engineering, analytics, or a related technical role. Strong experience with REST APIs, microservices, and data pipeline orchestration. Proficient in SQL and scripting languages (Python, Bash, PowerShell). Experience with data warehousing, ETL design, and industrial datasets. Familiarity with on-prem and cloud environments. Excellent analytical, communication, and problem-solving skills. Preferred/Bonus Skills Experience integrating data from PLCs or industrial protocols. Familiarity with Power BI, MES, or CMMS tools. Experience applying cybersecurity standards to data infrastructure. Knowledge of manufacturing environments, especially in metals or high-spec industries.

Job Title: Senior Software Engineer / Quant Developer (JG4 Level) Duration: Long-term contract with possibility of extension The Senior Data Engineer will design and build robust data foundations and end-to-end data solutions to enable the business to maximize value from data. This role plays a critical part in fostering a data-driven culture across both IT and business stakeholder communities. The Senior Data Engineer will act as a subject matter expert (SME), lead solution design and delivery, mentor junior engineers, and translate Data Strategy and Vision into scalable, high-quality IT solutions. Key Responsibilities Design, build, and maintain enterprise-grade data foundations and end-to-end data solutions. Serve as a subject matter expert in data engineering, data modeling, and solution architecture. Translate business data strategy and vision into scalable technical solutions. Mentor and guide junior data engineers and contribute to continuous capability building. Drive the rollout and adoption of Data Foundation initiatives across the business. Coordinate change management, incident management, and problem management processes. Present insights, reports, and technical findings to key stakeholders. Drive implementation efficiency across pilots and future projects to reduce cost, accelerate delivery, and maximize business value. Actively contribute to community initiatives such as Centers of Excellence (CoE) and Communities of Practice (CoP). Collaborate effectively with both technical teams and business leaders. Key Characteristics Highly curious technology expert with a continuous learning mindset. Strong data-domain expertise with deep technical focus. Excellent communicator who can engage both technical and non-technical stakeholders. Trusted advisor to leadership and cross-functional teams. Strong driver of execution, quality, and delivery excellence. Mandatory Skills Cloud Platforms: AWS, Azure, SAP - Expert Level ELT: Expert Level Data Modeling: Expert Level Data Integration & Ingestion Data Manipulation & Processing DevOps & Version Control: GitHub, GitHub Actions, Azure DevOps Data & Analytics Tools: Data Factory, Databricks, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube, PyTest Optional / Nice-to-Have Skills Experience leading projects or running a Scrum team. Experience with BPC and Planning. Exposure to external technical ecosystems. Documentation using MkDocs.

Title: Data Analytics Engineer Type: 6 Month Contract (Full-time is possible after contract period) Schedule: Hybrid (3-4 days onsite) Sector: Oil & Gas Overview: You will be instrumental in developing and maintaining data models while delivering insightful analyses of maintenance operations, including uptime/downtime, work order metrics, and asset health. Key Responsibilities: Aggregate and transform raw data from systems such as CMMS, ERP, and SCADA into refined datasets and actionable reports/visualizations using tools like SQL, Python, Power BI, and/or Spotfire. Own the creation and maintenance of dashboards for preventative and predictive maintenance. Collaborate cross-functionally to identify data requirements, key performance indicators (KPIs), and reporting gaps. Ensure high data quality through rigorous testing, validation, and documentation. Qualifications and Skills: Bachelor's degree required. Proficiency in Python and SQL is essential. Knowledge of API rules and protocols. Experience organizing development workflows using GitHub. Familiarity with Machine Learning is a plus. Preference for candidates with experience in water midstream/infrastructure or Oil & Gas sectors. Expertise in dashboard creation using tools like Tableau, Spotfire, Excel, or Power BI. Ability to clearly communicate technical concepts to non-technical stakeholders. Strong organizational skills and a customer-service mindset. Capability to work independently or collaboratively with minimal supervision. Exceptional analytical and problem-solving skills, with a strategic approach to prioritization. Ability to analyze data, situations, and processes to make informed decisions or resolve issues, with regular communication to management. Excellent written and verbal communication skills.

Staff Data Engineer - Houston, TX or US Remote A Series B funded startup who are building the infrastructure that powers how residential HVAC systems are monitored, maintained, and serviced are looking for a Staff Data Engineer to join their team. What will I be doing: Help architect and build the core data platform that powers the company's intelligence - from ingestion and transformation to serving and analytics Design and implement scalable data pipelines (batch and streaming) across diverse data sources including IoT sensors, operational databases, and external systems Work with high-performance database technologies Define foundational data models and abstractions that enable high-quality, consistent access for analytics, product, and ML workloads Collaborate with AI/ML, Product, and Software Engineering teams to enable data-driven decision-making and real-time intelligence Establish engineering best practices for data quality, observability, lineage, and governance Evaluate and integrate modern data technologies (e.g., Redshift, S3, Spark, Airflow, dbt, Kafka, Databricks, Snowflake, etc.) to evolve the platform's capabilities Mentor engineers across teams What are we looking for: 8+ years of experience as a software or data engineer, including ownership of large-scale data systems used for analytics or ML Deep expertise in building and maintaining data pipelines and ETL frameworks (Python, Spark, Airflow, dbt, etc.) Strong background in modern data infrastructure Proficiency with SQL and experience designing performant, maintainable data models Solid understanding of CI/CD, infrastructure-as-code, and observability best practices Experience enabling ML workflows and understanding of data needs across the model lifecycle Comfort working with cloud-native data platforms (AWS preferred) Strong software engineering fundamentals Excellent communicator What's in it for me: Competitive compensation up to $250,000 dependent on experience and location Foundational role as the first Staff Data Engineer Work hand-in-hand with the Head of Data to design and implement systems, pipelines, and abstractions that make us an AI-native company Apply now for immediate consideration!

We are seeking an experienced Data Engineer (5+ years) to join our Big Data & Advanced Analytics team. This role partners closely with Data Science and key business units to solve real-world midstream oil and gas challenges using machine learning, data engineering, and advanced analytics. The ideal candidate brings strong technical expertise and thought leadership to help mature and scale the organization's data engineering practice. Must-Have Skills Python (Pandas, NumPy, PyTest, Scikit-Learn) SQL Apache Airflow Kubernetes CI/CD Git Test-Driven Development (TDD) API development Working knowledge of Machine Learning concepts Key Responsibilities Build, test, and maintain scalable data pipeline architectures Work independently on analytics and data engineering projects across multiple business functions Automate manual data flows to improve reliability, speed, and reusability Develop data-intensive applications and APIs Design and implement algorithms that convert raw data into actionable insights Deploy and operationalize mathematical and machine learning models Support data analysts and data scientists by enabling data processing automation and deployment workflows Implement and maintain data quality checks to ensure accuracy, completeness, and consistenc

We are seeking a highly skilled Data Engineer with 5+ years of hands-on experience to design, build, and optimize scalable data pipelines and modern data platforms. The ideal candidate will have strong expertise in cloud data engineering, ETL/ELT development, real-time streaming, and data modeling, with a solid understanding of distributed systems and best engineering practices. Design, develop, and maintain scalable ETL/ELT pipelines for ingestion, transformation, and processing of structured and unstructured data. Build real-time and batch data pipelines using tools such as Kafka, Spark, AWS Glue, Kinesis, or similar technologies. Develop and optimize data models, warehouse layers, and high-performance data architectures. Implement data quality checks, data validation frameworks, and ensure data reliability and consistency across systems. Collaborate with Data Analysts, Data Scientists, and cross-functional teams to deliver efficient and accessible data solutions. Deploy and manage data infrastructure using AWS / Azure / GCP cloud services. Write clean, efficient, and reusable code in Python/Scala/SQL. Monitor pipeline performance, troubleshoot issues, and drive continuous improvement. Implement CI/CD pipelines, version control, and automation for production workloads. Ensure data governance, security, and compliance in all engineering workflows. Required Skills & Qualifications 5+ years of experience as a Data Engineer in a production environment. Strong proficiency in Python, SQL, and distributed processing frameworks (Spark, PySpark, Hadoop). Hands-on experience with cloud platforms: AWS, Azure, or GCP. Experience with streaming technologies: Kafka, Kinesis, Spark Streaming, Flink (any). Strong understanding of data warehousing concepts (Star/Snowflake schemas, dimensional modeling). Experience with ETL/ELT tools (Glue, Airflow, DBT, Informatica, etc.). Solid understanding of DevOps practices: Git, CI/CD, Terraform/CloudFormation (bonus). Experience working with relational and NoSQL databases (Redshift, Snowflake, BigQuery, DynamoDB, etc.). Excellent problem-solving, communication, and analytical skills.

Minimum 7 years of relevant work experience in data engineering, with at least 2 years in a data modeling. Strong technical foundation in Python, SQL, and experience with cloud platforms (Azure,). Deep understanding of data engineering fundamentals, including database architecture and design, Extract, transform and load (ETL) processes, data lakes, data warehousing, and both batch and streaming technologies. Experience with data orchestration tools (e.g., Airflow), data processing frameworks (e.g., Spark, Databricks), and data visualization tools (e.g., Tableau, Power BI). Proven ability to lead a team of engineers, fostering a collaborative and high-performing environment.

Now Hiring: Senior Data Engineer (GCP / Big Data / ETL) Duration: 6 Months (Possible Extension) We're seeking an experienced Senior Data Engineer with deep expertise in Data Warehousing, ETL, Big Data, and modern GCP-based data pipelines. This role is ideal for someone who thrives in cross-functional environments and can architect, optimize, and scale enterprise-level data solutions on the cloud. Must-Have Skills (Non-Negotiable) 9+ years in Data Engineering & Data Warehousing 9+ years hands-on ETL experience (Informatica, DataStage, etc.) 9+ years working with Teradata 3+ years hands-on GCP and BigQuery Experience with Dataflow, Pub/Sub, Cloud Storage, and modern GCP data pipelines Strong background in query optimization, data structures, metadata & workload management Experience delivering microservices-based data solutions Proficiency in Big Data & cloud architecture 3+ years with SQL & NoSQL 3+ years with Python or similar scripting languages 3+ years with Docker, Kubernetes, CI/CD for data pipelines Expertise in deploying & scaling apps in containerized environments (K8s) Strong communication, analytical thinking, and ability to collaborate across technical & non-technical teams Familiarity with AGILE/SDLC methodologies Key Responsibilities Build, enhance, and optimize modern data pipelines on GCP Implement scalable ETL frameworks, data structures, and workflow dependency management Architect and tune BigQuery datasets, queries, and storage layers Collaborate with cross-functional teams to define data requirements and support business objectives Lead efforts in containerized deployments, CI/CD integrations, and performance optimization Drive clarity in project goals, timelines, and deliverables during Agile planning sessions 📩 Interested? Apply now or DM us to explore this opportunity! You can share resumes at ******************* OR Call us on *****************

Must Haves: Strong proficiency in Python; 5+ years' experience. Expertise in Fast API and microservices architecture and coding Linking python based apps with sql and nosql db's Deployments on docker, Kubernetes and monitoring tools Experience with Automated testing and test-driven development Git source control, git actions, ci/cd , VS code and copilot Expertise in both on prem sql dbs (oracle, sql server, Postgres, db2) and no sql databases Working knowledge of data warehousing and ETL Able to explain the business functionality of the projects/applications they have worked on Ability to multi task and simultaneously work on multiple projects. NO CLOUD - they are on prem Day to Day: Insight Global is looking for a Python Data Engineer for one of our largest oil and gas clients in Downtown Houston, TX. This person will be responsible for building python-based relationships between back-end SQL and NoSQL databases, architecting and coding Fast API and Microservices, and performing testing on back-office applications. The ideal candidate will have experience developing applications utilizing python and microservices and implementing complex business functionality utilizing python.

Junior Data Engineer DESCRIPTION: BeaconFire is based in Central NJ, specializing in Software Development, Web Development, and Business Intelligence; looking for candidates who are good communicators and self-motivated. You will play a key role in building, maintaining, and operating integrations, reporting pipelines, and data transformation systems. Qualifications: Passion for data and a deep desire to learn. Master's Degree in Computer Science/Information Technology, Data Analytics/Data Science, or related discipline. Intermediate Python. Experience in data processing is a plus. (Numpy, Pandas, etc) Experience with relational databases (SQL Server, Oracle, MySQL, etc.) Strong written and verbal communication skills. Ability to work both independently and as part of a team. Responsibilities: Collaborate with the analytics team to find reliable data solutions to meet the business needs. Design and implement scalable ETL or ELT processes to support the business demand for data. Perform data extraction, manipulation, and production from database tables. Build utilities, user-defined functions, and frameworks to better enable data flow patterns. Build and incorporate automated unit tests, participate in integration testing efforts. Work with teams to resolve operational & performance issues. Work with architecture/engineering leads and other teams to ensure quality solutions are implemented, and engineering best practices are defined and adhered to. Compensation: $65,000.00 to $80,000.00 /year BeaconFire is an e-verified company. Work visa sponsorship is available.