> Markdown version of [/jobs/ext/3691329-sr-data-engineer](https://www.wearedevelopers.com/jobs/ext/3691329-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:** SFE PARTNERS LLC - **Location:** McLean, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, Profiling, Information Engineering, Data Mapping, Data Profiling, Python (Programming Language), Standard Sql, SQL Databases, Software Vulnerability Management, Snowflake, Apache Spark, Build Management, Data Lakes, AWS Glue, Api Design, Data Pipelines, Databricks - **Published:** October 11, 2026 - **Apply:** https://www.careerjet.com/jobad/us3ccb356d2cf24d0df736a2d32781c8af ## About the Role Must-Have: * Python * Spark * SQL * Airflow * AWS Glue * Databricks Preferred/Nice to Have: * Delta Lake * Snowflake * API experience Strong Differentiators: * Data profiling and analysis * Data mapping * Production support experience * Vulnerability remediation * Experience supporting and maintaining pipelines in production environments Candidate Profile * Ideal experience level: 5-10 years, with 5-7 years being a strong target range. * Candidates should demonstrate the ability to: * Design and build data pipelines * Support and troubleshoot production workloads * Perform data analysis, profiling, and mapping * Own operational support responsibilities in addition to development work ## Description One-day interview loop consisting of: * Python Coding Assessment * Candidates must write code during the interview. * Approximately 1.5 hours of total coding assessments. * SQL Assessment * Must be able to write and explain SQL solutions. * System Design / Architecture Discussion * Data engineering architecture and design-focused questions. Suppliers are encouraged to conduct their own technical screening prior to submission, as the hiring team prefers candidates who have already been vetted. Additional Notes * Work is primarily batch-processing focused. * Databricks will be used heavily during discovery and proof-of-concept phases before production implementation.