Senior data scientist jobs in Alton, TX

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

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.

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. Here's the job details, Data Scientist with Gen Ai and Python experience Plano, TX- 5 days Onsite 18+ Months Job Overview: Competent Data Scientist, who is independent, results driven and is capable of taking business requirements and building out the technologies to generate statistically sound analysis and production grade ML models DS skills with GenAI and LLM Knowledge, Expertise in Python/Spark and their related libraries and frameworks. Experience in building training ML pipelines and efforts involved in ML Model deployment. Experience in other ML concepts - Real time distributed model inferencing pipeline, Champion/Challenger framework, A/B Testing, Model. Familiar with DS/ML Production implementation. Excellent problem-solving skills, with attention to detail, focus on quality and timely delivery of assigned tasks. Azure cloud and Databricks prior knowledge will be a big plus. 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.

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

********* NO THIRD PARTIES PLEASE******** This is a contract to hire position for a very stable organization. Great teammates and a great opportunity for growth and a long career. I-10 West Houston area location for the company. ****The position is REMOTE; however, I am seeking a local Houston candidate as there will be periodic times to come into the office for team meetings. Texas area candidates that are willing to relocate to Houston or at the very least commit to coming to periodic on-site team meetings. Summary: Seeking a Data Modeler that will be responsible for cleaning up to optimize workflows. This position will require strong hands-on Data Modeler experience. MUST have strong Microsoft Fabric experience, which is a key component for this particular role. Requirements: - 7+ years of Data Modeling experience - 3+ years in data modeling or analytics engineering with strong SQL. - Must have 2-3 years plus of hands-on Microsoft Fabric experience. - Lakehouse/Warehouse, One Lake, Delta tables, Dataflows Gen2 or Pipelines; familiarity with SQL endpoint usage. - Star schemas; fact types (transactional, periodic snapshot, accumulating); bridge tables for M: N; degenerate and junk dimensions. - SCD Type 1/2 with MERGE; effective/expiry dating; handling late-arriving data. - Power BI semantic modeling and DAX - Clean tabular model design; CALCULATE/KEEPFILTERS/USERELATIONSHIP; date intelligence; semi-additive measures; model properties (data types, sort-by, formatting). - Incremental refresh; basic aggregations; RLS. - Define tests (unique/not-null/accepted values), document metrics, manage endorsements; apply sensitivity labels for PII/regulated data. Translate stakeholder requirements into grain/facts/dimensions and certified measures; collaborate across DE, BI, and business teams.

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.

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

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.

Title: Junior Data Reporting Engineer MUST Business Intelligence SQL Dashboard Development (Tableau, BO, OBI, Power BI) Python Job Description: Implement and maintain data analysis scripts using SQL and Python. Develop and support reports and dashboards using Plx Data Studio Looker. Improve and develop new and existing dashboards supporting business growth. Monitor performance and implement the necessary infrastructure optimization. Demonstrate the ability and willingness to learn quickly and complete large volumes of work with high quality. Demonstrate excellent collaboration, interpersonal communication, and written skills with the ability to work in a team environment. Minimum Qualifications: 2+ years of solid hands-on experience with complex SQL scripting and Dashboard development. Hands-on experience with design, development, and support of data analysis. Experience with data platform and visualization technologies such as dashboards, Data Studio, Looker, SQL, and BigQuery. Strong design and development skills with meticulous attention to detail. Familiarity with Agile Software Development practices and working in an agile environment. Strong analytical, troubleshooting, and organizational skills. Ability to analyze and troubleshoot complex issues, and proficiency in multitasking. BS degree in Computer Science, Math, Statistics, or equivalent academic credentials.

About Us Longbridge Securities, founded in March 2019 and headquartered in Singapore, is a next-generation online brokerage platform. Established by a team of seasoned finance professionals and technical experts from leading global firms, we are committed to advancing financial technology innovation. Our mission is to empower every investor by offering enhanced financial opportunities. What You'll Do As part of our global expansion, we're seeking a Data Engineer to design and build batch/real-time data warehouses and maintain data platforms that power trading and research for the US market. You'll work on data pipelines, APIs, storage systems, and quality monitoring to ensure reliable, scalable, and efficient data services. Responsibilities: Design and build batch/real-time data warehouses to support the US market growth Develop efficient ETL pipelines to optimize data processing performance and ensure data quality/stability Build a unified data middleware layer to reduce business data development costs and improve service reusability Collaborate with business teams to identify core metrics and data requirements, delivering actionable data solutions Discover data insights through collaboration with the business owner Maintain and develop enterprise data platforms for the US market Qualifications 7+ years of data engineering experience with a proven track record in data platform/data warehouse projects Proficient in Hadoop ecosystem (Hive, Kafka, Spark, Flink), Trino, SQL, and at least one programming language (Python/Java/Scala) Solid understanding of data warehouse modeling (dimensional modeling, star/snowflake schemas) and ETL performance optimization Familiarity with AWS/cloud platforms and experience with Docker, Kubernetes Experience with open-source data platform development, familiar with at least one relational database (MySQL/PostgreSQL) Strong cross-department collaboration skills to translate business requirements into technical solutions Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related fields Comfortable working in a fast-moving fintech/tech startup environment Qualifications 7+ years of data engineering experience with a proven track record in data platform/data warehouse projects Proficient in Hadoop ecosystem (Hive, Kafka, Spark, Flink), Trino, SQL, and at least one programming language (Python/Java/Scala) Solid understanding of data warehouse modeling (dimensional modeling, star/snowflake schemas) and ETL performance optimization Familiarity with AWS/cloud platforms and experience with Docker, Kubernetes Experience with open-source data platform development, familiar with at least one relational database (MySQL/PostgreSQL) Strong cross-department collaboration skills to translate business requirements into technical solutions Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related fields Comfortable working in a fast-moving fintech/tech startup environment Proficiency in Mandarin and English at the business communication level for international team collaboration Bonus Point: Experience with DolphinScheduler and SeaTunnel is a plus

I want to do 3 rounds of interviews: Teams virtual tech interview with senior developers Karat screening In person interview with managers and directors 5+ years of experience in data engineering, sql and nosql databases like oracle, sql server, postgres, db2, elastic, mongo db and advanced python skills. Advanced application development experience with implementing business logic utilizing SQL procedures and NOSQL utilities Experience with design and development of scalable and performant processes Expert in Python development and fast API microservices what IDEs and tools did they use to code and test? Development experience with real time user interactive applications and communicate between UI and database what protocols/data formats did they use to interact between db and UI

Our client is seeking an experienced Data Engineer (5+ years) to join their Big Data and Advanced Analytics team. In this role, you'll collaborate closely with the Data Science team and various business units to tackle real-world challenges in the oil and gas midstream sector using machine learning, AI, and data-driven solutions. You'll also play a key role in shaping and advancing the organization's data engineering practices. Job Description Design, build, test, and maintain scalable data pipelines Independently handle analytics projects across multiple business functions Automate manual data processes for efficiency and scalability Develop data-intensive applications and APIs Create algorithms that turn raw data into actionable insights Deploy and operationalize machine learning and mathematical models Support data analysts and data scientists by streamlining data processing and model deployment Ensure data accuracy and consistency through quality checks Skills Required 5+ years of professional IT experience, ideally in network security engineering Strong experience with: Python (Pandas, NumPy, Pytest, Scikit-Learn) SQL Apache Airflow Kubernetes CI/CD pipelines Git version control Test-Driven Development (TDD) API development Familiarity with machine learning concepts and applications Education/Certifications High School Diploma or GED GAS Global Services LLC is an Equal Opportunity Employer. Employment Decision are made without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factors protected by applicable federal, state or local laws. JOB-10045560

MUST BE USC or Green Card; No vendors GCP Data Engineer/Lead Onsite Required Qualifications: 9+ years' experience and hands on with Data Warehousing. 9+ years of hands on ETL (e.g., Informatica/DataStage) experience 3+ years of hands-on Big query 3+ years of hands on GCP 9+ years of Teradata hands on experience 9+ years working in a cross-functional environment. 3+ years of hands-on experience with Google Cloud Platform services like Big Query, Dataflow, Pub/Sub, and Cloud Storage 3+ years of hands-on experience building modern data pipelines with GCP platform 3+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management 3+ years of experience with SQL, NoSQL 3+ years of experience in data engineering with a focus on microservices-based data solutions 3+ years of containerization (Docker, Kubernetes) and CI/CD for data pipeline 3+ years of experience with Python (or a comparable scripting language) 3+ years of experience with Big data and cloud architecture 3+ years of experience with deployment/scaling of apps on containerized environment (Kubernetes,) Excellent oral and written communications skills; ability to interact effectively with all levels within the organization. Working knowledge of AGILE/SDLC methodology Excellent analytical and problem-solving skills. Ability to interact and work effectively with technical & non-technical levels within the organization. Ability to drive clarity of purpose and goals during release and planning activities. Excellent organizational skills including ability to prioritize tasks efficiently with high level of attention to detail. Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.

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 *****************

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.

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.

AZURE DATA ENGINEER with DATA FACTORY. Databrick certified 3 days a week onsite, can be based out of Irving TX or Houston TX. Rate is 45 W2.

W2 Contract to Hire Role with Monthly Travel to the Dallas Texas area We are looking for a highly skilled and independent Data Engineer to support our analytics and data science teams, as well as external client data needs. This role involves writing and optimizing complex SQL queries, generating client-specific data extracts, and building scalable ETL pipelines using Azure Data Factory. The ideal candidate will have a strong foundation in data engineering, with a collaborative mindset and the ability to work across teams and systems. Duties/Responsibilities:Develop and optimize complex SQL queries to support internal analytics and external client data requests. Generate custom data lists and extracts based on client specifications and business rules. Design, build, and maintain efficient ETL pipelines using Azure Data Factory. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality solutions. Work with Salesforce data; familiarity with SOQL is preferred but not required. Support Power BI reporting through basic data modeling and integration. Assist in implementing MLOps practices for model deployment and monitoring. Use Python for data manipulation, automation, and integration tasks. Ensure data quality, consistency, and security across all workflows and systems. Required Skills/Abilities/Attributes: 5+ years of experience in data engineering or a related field. Strong proficiency in SQL, including query optimization and performance tuning. Experience with Azure Data Factory, with git repository and pipeline deployment. Ability to translate client requirements into accurate and timely data outputs. Working knowledge of Python for data-related tasks. Strong problem-solving skills and ability to work independently. Excellent communication and documentation skills. Preferred Skills/ExperiencePrevious knowledge of building pipelines for ML models. Extensive experience creating/managing stored procedures and functions in MS SQL Server 2+ years of experience in cloud architecture (Azure, AWS, etc) Experience with ‘code management' systems (Azure Devops) 2+ years of reporting design and management (PowerBI Preferred) Ability to influence others through the articulation of ideas, concepts, benefits, etc. Education and Experience: Bachelor's degree in a computer science field or applicable business experience. Minimum 3 years of experience in a Data Engineering role Healthcare experience preferred. Physical Requirements:Prolonged periods sitting at a desk and working on a computer. Ability to lift 20 lbs.

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.