Senior data scientist jobs in El Paso, TX

Data Scientist (F2F interview) 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.

One of our staffing partners is helping a financial client hire a Data Scientist with data analyst skills Salary offered $60-75k per year Direct applicants only no c2c or company candidates due to low margins. The staffing company or client will reach directly to the applicants. Responsibilities: Design, train, and fine-tune Large Language Models (LLMs) for various applications experience with sql, excel, Powerbi Collaborate with cross-functional teams to integrate AI into real-world applications Analyze and preprocess massive datasets for AI-driven insights Proficiency in Python, TensorFlow, PyTorch, and Hugging Face libraries Knowledge of transformer architectures, attention mechanisms, and reinforcement learning Experience with fine-tuning and optimizing foundation models Familiarity with cloud-based AI environments (AWS, Azure, or GCP) Experience with AI model deployment and optimization techniques

About Company, Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters. Data Scientist with DataBricks experience Plano, TX (5 Days Onsite) Interview Mode:-Phone & F2F Rate Range $40 to $47 hr W2 All Inc Job Overview We are seeking a highly skilled, independent, and results-driven Data Scientist with strong expertise in GenAI, LLMs, Python, Spark, Databricks, and End-to-End ML Model Development. The ideal candidate will be capable of translating business needs into scalable analytical solutions and delivering production-grade machine learning models. Key Responsibilities Build statistically sound analyses and production-ready ML models. Develop and optimize models using H2O frameworks (XGBoost, Logistic Regression, Neural Networks, Random Forest). Work extensively with MongoDB and NoSQL datasets. Design, develop, and maintain ML training pipelines and support ML model deployment. Utilize Databricks, Hadoop ecosystem, and PySpark for large-scale data preparation and modeling. Implement advanced ML concepts such as: Real-time distributed model inferencing pipelines A/B Testing Champion/Challenger frameworks Develop scalable workflows using Python, Spark, and related libraries. Use Unix/Linux and shell scripting for automation and environment management. Support ML production implementation, monitoring, and troubleshooting. Deliver high-quality solutions with strong attention to detail and timely execution. Required Skills & Qualifications Python & Spark Expertise Databricks & PySpark Experience GenAI & LLM Knowledge H2O Model Development (XGBoost, Logistic Regression, Neural Networks, Random Forest) MongoDB / NoSQL Databases Hadoop Ecosystem ML Pipeline Development & Deployment Real-Time Model Inferencing Champion/Challenger Frameworks & A/B Testing Unix/Linux & Shell Scripting DS/ML Production Implementation Preferred Skills Azure Cloud experience Advanced experience with Databricks in cloud environments Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment.

At least 8-10 years of data modelling experience, preferably with Fortune 500 companies Ability to deliver independently with minimal supervision. Ability to collaborate with users to capture data modelling requirements. Ability to collaborate with client architects to review and approve data models. 3-5 years of Experience with Erwin Data Modelling tool Ability to reverse engineer data models from DDLs, Databases Conceptual Data Modelling experience Logical Data Modelling experience Physical Data Modelling experience Ability to create DDLs for creation of physical database objects. Experience with Kimball, Inmon modelling methodology Ability to work with client defined data modelling guidelines, and standards. Ability to work on multiple data models concurrently. RDBMS experience e.g., Snowflake, Oracle, SQL Server Ability to create data flows. Ability to lead offshore team. Experience with Agile Methodology / Approach Excellent written and verbal communication skills Optional Skills (Nice to have) Insurance industry experience Data Domain Modelling experience Data Engineering experience Solution Design experience Experience working with Jira Experience using Confluence / Wiki

Plano TX- Nearby candidates only W2 Candidates Must Have: 5+ years of experience with data modeling, warehousing, analysis & data profiling experience and ability to identify trends and anomalies in the data Experience on AWS technologies like S3, AWS Glue, EMR, and IAM roles/permissions Experience with one or more query language (e.g., SQL, PL/SQL, DDL, SparkSQL, Scala) Experience working with relational database such as Teradata and handling both structured and unstructured datasets Data Modeling tools (Any of - Erwin, Power Designer, ER Studio) Preferred / Ideal to have - Proficiency in Python Experience with NoSQL, non-relational databases / data stores (e.g., object storage, document or key-value stores, graph databases, column-family databases) Experience with Snowflake and Databricks

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.

Data Engineer III Duration: Contract We are seeking a highly skilled and experienced Data Engineer III to join our team in Austin, Texas. The ideal candidate will be responsible for designing, developing, and maintaining data pipelines and systems to support our organization's data needs. This role requires a deep understanding of data engineering principles, strong problem-solving skills, and the ability to work collaboratively in a fast-paced environment. Responsibilities: Design, develop, and maintain scalable data pipelines and systems. Collaborate with cross-functional teams to understand data requirements and deliver solutions. Optimize and improve data workflows for efficiency and reliability. Ensure data quality and integrity through robust testing and validation processes. Monitor and troubleshoot data systems to ensure smooth operations. Stay updated with the latest trends and technologies in data engineering. Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in programming languages such as Python, Java, or Scala. Experience with big data technologies like Hadoop, Spark, or Kafka. Proficiency in SQL and database management systems. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Excellent problem-solving and analytical skills. Strong communication and teamwork abilities. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit ***************** At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $70 - $75 The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by appliable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at ***************. To report any concerns, please email us at *******************

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.

About the Company: This is a fantastic opportunity to join an internationally renowned powerhouse within the supply chain industry. You will have the opportunity to work on a variety of different projects across teams. In this position, you'll be the architect of our data pipelines, instrumental in operationalizing data & advanced analytics to drive organizational outcomes. Role: In this position, you'll be the architect of our data pipelines, instrumental in operationalizing data & advanced analytics to drive organizational outcomes. Your responsibilities will include: Strategic: Provide architectural input to project teams, aligning solutions with long-term data warehouse strategy. Data Management: Navigate various data architectures like Data Warehouse, Data Lake, Data Hub, and Data Vault, ensuring seamless integration and governance. Integration: Harness the power of ETL/ELT, data replication, message-oriented data movement, and API-based data acquisition to work with large, heterogeneous datasets. Data: Analyze large datasets, uncovering insights and anomalies that fuel informed decision-making. Requirements: Snowflake Proficiency in complex SQL code and DevOps capabilities. Experience with ETL tools and open-source/commercial message queuing technologies. Strong Python skills for data manipulation and automation. Preferred Experience: Familiarity with SQL Server, SAP Hana, Tableau, Power BI, dbt, and Azure Data Factory. Experience in building forecasting models including linear regression and time-series analysis. This role is based in Houston and they work on a hybrid model. Compensation offered is in the region of $100,000-$150,000 with additional bonus compensation dependent on company performance. The bonus is approximately 15%. If interested, please apply. Equal Opportunity Employer/Disability/Veterans.

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.

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

Our client is seeking an Azure Data Engineer to join their team! This position is located in Irving, Texas. THIS ROLE REQUIRES AN ONSITE INTERVIEW IN IRVING, please only apply if you are local and available to interview onsite. Duties: Lead the design, architecture, and implementation of key data initiatives and platform capabilities Optimize existing data workflows and systems to improve performance, cost-efficiency, identifying and guiding teams to implement solutions Lead and mentor a team of 2-5 data engineers, providing guidance on technical best practices, career development, and initiative execution Contribute to the development of data engineering standards, processes, and documentation, promoting consistency and maintainability across teams while enabling business stakeholders Desired Skills/Experience: Bachelor's degree or equivalent in Computer Science, Mathematics, Software Engineering, Management Information Systems, etc. 5+ years of relevant work experience in data engineering Strong technical skills in SQL, PySpark/Python, Azure, and Databricks Deep understanding of data engineering fundamentals, including database architecture and design, ETL, etc. Benefits: Medical, Dental, & Vision Insurance Plans Employee-Owned Profit Sharing (ESOP) 401K offered The approximate pay range for this position starting at $140-145,000+. 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.

Hello, Role: Data Engineering & Analytics Consultant I am looking for EX-apple employee candidates Note: Data engineering, Advance proficiency in Python, SQL with 4-5 years exp. Job Overview : We are seeking a Software Engineer with strong SQL and Python skills to develop reliable data pipelines, optimize complex workflows, and deliver scalable data products that empower decision-making across Apple's ecosystem. Key Responsibilities: Design, build, and optimize ETL/ELT data pipelines using Python, SQL, and modern orchestration tools. Develop and maintain data models, APIs, and microservices that enable analytical and operational use cases. Work closely with cross-functional partners (Data Science, Product, Finance, and Operations) to translate business needs into engineering solutions. Apply software engineering best practices (version control, CI/CD, testing, observability) to data workflows. Optimize data quality, scalability, and latency across distributed systems (Snowflake, Spark, Databricks, etc.). Participate in architecture discussions on data warehousing, event streaming, and ML data pipelines. Ensure compliance with Apple's privacy, security, and governance standards in all data operations. Minimum Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. 3-7 years of experience in software or data engineering. Advanced proficiency in Python (Pandas, PySpark, or similar frameworks). Strong SQL expertise - ability to write and optimize complex queries and stored procedures. Proven experience with data modeling, schema design, and performance tuning. Experience building or orchestrating workflows using Airflow, Dagster, or similar tools. Solid understanding of APIs, CI/CD pipelines, Git, and containerization (Docker/Kubernetes).

Our Midstream Oil and Gas client is seeking a skilled Data Engineer to design, build, and maintain scalable data infrastructure that supports advanced analytics and business intelligence initiatives. You will work closely with data scientists, analysts, and software engineers to ensure data availability, quality, and reliability across the organization. Key Responsibilities Design, develop, and maintain data pipelines and ETL/ELT processes for collecting, transforming, and storing data from multiple sources Build and optimize data models, data warehouses, and data lakes for analytics and reporting. Collaborate with stakeholders to define data architecture and ensure data integrity, consistency, and security Implement and maintain data quality frameworks, monitoring, and alerting systems. Work with cloud platforms (AWS, Azure, or GCP) to deploy scalable data infrastructure Support the integration of real-time streaming data using tools like Kafka, Kinesis, or Spark Streaming Automate workflows using orchestration tools such as Airflow, Prefect, or Dagster Ensure compliance with data governance, security, and privacy standards (e.g., GDPR, HIPAA). Troubleshoot data-related issues and optimize performance of queries and pipelines Required Qualifications 7+ years of experience as a Data Engineer or similar role Strong proficiency in SQL and a programming language such as Python Hands-on experience with ETL frameworks, data warehousing, and big data tools (e.g., Spark, Hadoop). Experience with cloud-based data solutions such as AWS Redshift, Snowflake, BigQuery, or Azure Synapse. Proficiency with data orchestration and workflow automation tools Solid understanding of data modeling, data architecture, and API integration

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

· 12+ Years of Data Engineer. · 4+ years of hands-on experience in data engineering, including data lake infrastructure, data warehousing, and data analytics tools. · Cloud data engineering experience on azure. Deep understanding of azure services like data factory, data bricks, and machine learning. Azure certification is a plus. · Strong proficiency in SQL, python and pyspark. Proven ability to optimize SQL queries and performance tune data pipelines. · Experience in building and operating highly available, distributed data pipelines for large-scale data ingestion, processing, and extraction. · Experience integrating multi-cloud services with on-premises technologies. Strong understanding of data modelling processes. · Proven ability to solve complex data problems, collaborate effectively with cross-functional teams, and deliver high-quality solutions.

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.

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.

Job Title: GCP Data Engineer Employment Type: W2/CTH Client: Direct We are seeking a highly skilled Data Engineer with strong expertise in Python, SQL, and Google Cloud Platform (GCP) services. The ideal candidate will have 6-8 years of hands-on experience in building and maintaining scalable data pipelines, working with APIs, and leveraging GCP tools such as BigQuery, Cloud Composer, and Dataflow. Core Responsibilities: • Design, build, and maintain scalable data pipelines to support analytics and business operations. • Develop and optimize ETL processes for structured and unstructured data. • Work with BigQuery, Cloud Composer, and other GCP services to manage data workflows. • Collaborate with data analysts and business teams to ensure data availability and quality. • Integrate data from multiple sources using APIs and custom scripts. • Monitor and troubleshoot pipeline performance and reliability. Technical Skills: o Strong proficiency in Python and SQL. o Experience with data pipeline development and ETL frameworks. • GCP Expertise: o Hands-on experience with BigQuery, Cloud Composer, and Dataflow. • Additional Requirements: o Familiarity with workflow orchestration tools and cloud-based data architecture. o Strong problem-solving and analytical skills. o Excellent communication and collaboration abilities.