> Markdown version of [/jobs/ext/4583911-sr-data-engineer](https://www.wearedevelopers.com/jobs/ext/4583911-sr-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Engineer - **Company:** Everforth Apex - **Location:** Fairfax, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Amazon S3, Information Systems, Continuous Integration, Information Engineering, Data Integrity, Relational Databases, Distributed Computing Environment, Distributed Data Store, Operational Databases, SQL Databases, Real Time Systems, Snowflake, Reliability of Systems, Pyspark, Information Technology, Data Lineage, AWS Glue, Apache Kafka, Data Management, Data Pipelines, Databricks - **Published:** November 5, 2026 - **Apply:** https://www.dice.com/job-detail/6df2620d-a48c-4122-a686-3d6d765dd648 ## About the Role Education: Bachelor's degree in Computer Science, Information Systems, or a related technical field is preferred. Experience: A minimum of 6 years of dedicated data engineering experience, specifically focused on distributed data processing and scalable pipelines. Technical Skills: Proven proficiency in PySpark, AWS Glue, Snowflake, Databricks, and SQL, alongside solid foundational knowledge of AWS data engineering services, S3-based lakes, and relational databases. Preferred Qualifications * Prior experience working within the financial services sector. * Hands-on experience with low-latency streaming and real-time processing tools such as Kinesis or Kafka. * Familiarity with CI/CD practices for data pipelines and Infrastructure as Code. ## Description * Design and construct brand-new production data pipelines to handle large volumes of distributed data. * Ensure data integrity across pipeline architectures by implementing advanced quality checks and data lineage tracking. * Take ownership of individual data domains and deliver reliable data engineering solutions independently. * Set up robust pipeline monitoring, alerting, and observability dashboards to maintain high system reliability. * Collaborate with a cross-functional team of engineers and analysts to extend data platforms into new consumer domains.