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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (Databricks / Spark) - **Company:** Savantis Solutions, LLC - **Location:** Columbus, OH, United States - **Experience:** Expert - **Salary:** $124,800.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Warehousing, DevOps, Python (Programming Language), Operational Databases, Performance Tuning, SQL Databases, Data Ingestion, Snowflake, Apache Spark, Git, Data Lakes, Pyspark, Apache Kafka, Data Management, Stream Processing, Software Version Control, Data Pipelines, Databricks - **Published:** June 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=7a88bae140fdb8d9 ## About the Role Do you have experience in Version control systems?, * 7+ years of experience in Data Engineering and Big Data technologies. * Strong hands-on experience with Databricks and Apache Spark (PySpark/Scala Spark). * Expertise in designing, developing, and optimizing large-scale ETL/ELT pipelines. * Strong experience with Python and SQL. * Experience working with cloud platforms such as AWS, Azure, or GCP. * Hands-on experience with Delta Lake, Data Lake architecture, and data modeling concepts. * Experience with workflow orchestration tools such as Airflow or similar. * Strong understanding of data warehousing concepts and performance tuning. * Experience with version control systems such as Git. * Ability to troubleshoot and optimize Spark jobs for performance and scalability., * Experience working in financial services or banking environments. * Familiarity with JPMC data platforms and enterprise data ecosystems. * Experience with Kafka, Snowflake, or other modern data technologies. * Knowledge of CI/CD processes and DevOps practices. * Databricks or Cloud certifications are a plus. ## Description We are seeking an experienced Data Engineer with strong expertise in Databricks and Apache Spark to join a high-performing data engineering team supporting enterprise-scale data initiatives at JPMC. The ideal candidate will have hands-on experience building scalable data pipelines, optimizing Spark workloads, and working with large datasets in cloud-based environments., * Design, develop, and maintain scalable data pipelines using Databricks and Spark. * Build and optimize batch and real-time data processing solutions. * Collaborate with business stakeholders, architects, and development teams to understand data requirements. * Perform data ingestion, transformation, cleansing, and validation activities. * Monitor and troubleshoot production data pipelines. * Implement data quality, governance, and security best practices. * Optimize Spark jobs and Databricks clusters for performance and cost efficiency. * Participate in code reviews and ensure adherence to development standards. ## 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) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [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) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## 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) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [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)