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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Bright Sol - **Location:** Alpharetta, GA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Apache HTTP Server, Microsoft Azure, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Migration, Data Warehousing, Dimensional Modeling, Python (Programming Language), Standard Sql, SQL Databases, Azure Data Factory, Snowflake, Git, Data Lakes, Pyspark, Luigi, Star Schema, Spark Streaming, Data Management, Azure Synapse Analytics, Data Pipelines, Jenkins, Databricks - **Published:** September 3, 2026 - **Apply:** https://www.dice.com/job-detail/a0230981-3a13-44e5-bda5-31aa6983619e ## About the Role **Experience:** 3+ Years ### MUST-HAVE TECHNOLOGIES **Databricks | Snowflake | Azure | Python | PySpark | SQL**, * 3+ years of hands-on Data Engineering experience * Strong **Python, PySpark & SQL** * Hands-on **Databricks & Snowflake** * Strong Azure Data Services experience * **Azure Data Factory (ADF), ADLS & Azure Synapse** * ETL/ELT pipeline development * Data Lake / Data Warehouse architecture * Databricks Notebooks, Jobs & Delta Lake * Data Modeling: Star Schema, Snowflake Schema & Dimensional Modeling * Orchestration: **Airflow, dbt, Luigi or similar** * Git & CI/CD * Jenkins or similar CI/CD tools * Data Quality, Governance, Security & Compliance ### NICE TO HAVE * Palantir Foundry * Unity Catalog * Spark Streaming / Real-Time Data Pipelines * IBM watsonx.data or similar AI data platforms * Apache Iceberg / Lakehouse technologies * GenAI / RAG / LangChain * MCP (Model Context Protocol) ## Description We are seeking a hands-on **Data Engineer** experienced in building, maintaining, troubleshooting, and optimizing modern cloud data pipelines., * Design and develop end-to-end data pipelines using **Databricks & Snowflake** * Build scalable ETL/ELT workflows using **Python, PySpark & SQL** * Develop Databricks notebooks, jobs, Delta Lake tables and workflows * Build Azure data solutions using **ADF, ADLS & Synapse** * Optimize Snowflake queries, clustering, storage, partitioning and materialized views * Implement data quality and governance processes * Develop streaming pipelines using Spark Streaming or similar technologies * Build and maintain CI/CD pipelines for data workflows * Troubleshoot production pipelines and resolve performance/data-quality issues * Collaborate with Data Scientists, Analysts, Engineers and Business Stakeholders * Support data migration initiatives in a fast-paced environment ### ️ CLIENT SCREENING - PLEASE READ This client is **extremely selective and closely reviews resumes**. Candidates should have **genuine, hands-on experience** with the technologies listed on their resume and must be able to explain their projects and technical contributions in detail during the interview. **DO NOT add or inflate technologies that the candidate cannot technically explain.** Candidates must confidently demonstrate experience with: Databricks Snowflake Azure PySpark Python SQL ETL/ELT Data Pipelines ### SUBMISSION DETAILS Please provide: Updated Resume LinkedIn Profile Current Location Visa Status Availability Confirmation of willingness to work **onsite 5 days/week** **Long-term opportunity with renewable SOW anticipated through the end of 2027.** #Hiring #DataEngineer #DataEngineering #Databricks #Snowflake #Azure #PySpark #Python #SQL #AzureDataFactory #ADLS #Synapse #DeltaLake #ETL #ELT #DataPipelines #Airflow #DBT #Spark #CloudJobs #PlanoJobs #AlpharettaJobs #NewJerseyJobs #ContractJobs ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)