Data Engineer in Arlington, VA (Hybrid - 3 Days Onsite)

We are seeking an experienced Data Engineer to join a newly established analytics and reporting team focused on automating data extraction, transformation, and reporting processes across multiple client engagements. This role will support a pilot initiative designed to improve how business stakeholders access and utilize data, with the opportunity to contribute to a growing Center of Excellence focused on data automation and analytics., * Design, develop, and maintain scalable data pipelines and ETL processes.

• Build and optimize Spark-based data processing solutions.
• Extract, transform, and integrate large datasets from enterprise data sources.
• Write and optimize complex SQL and Spark SQL queries.
• Develop Python-based data extraction, transformation, and reporting solutions.
• Work with Hadoop ecosystem technologies including HDFS, Ozone, and Hive.
• Support data quality validation, troubleshooting, and production issue resolution.
• Collaborate with data engineers, analysts, and business stakeholders to deliver reporting and analytics solutions.
• Contribute to process automation initiatives and continuous improvement efforts.
• Follow coding standards, version control practices, and data governance requirements.

The ideal candidate will have strong hands-on experience with Spark, Hadoop, Python, and SQL, along with a background working in large-scale data environments. This position involves developing and optimizing data pipelines, transforming complex datasets, and supporting reporting and analytics solutions used across multiple business functions., * Strong experience as a Data Engineer or similar data-focused role.

• Advanced experience with:
• Apache Spark (PySpark, Spark SQL)
• Hadoop Ecosystem (HDFS, Hive, YARN, Ozone)
• Python
• SQL
• Experience building and maintaining ETL/data pipeline solutions.
• Strong understanding of data modeling, data integration, and data warehousing concepts.
• Experience working with large-scale transactional or analytical data environments.
• Ability to identify and resolve data quality and performance issues.
• Strong communication skills and ability to work with both technical and non-technical stakeholders., * Experience in financial services, banking, payments, fintech, or transaction-processing environments.
• Experience working with large enterprise data platforms.
• Familiarity with reporting and analytics-focused data engineering solutions.
• Prior experience supporting client-facing analytics initiatives., * Hybrid schedule with three days onsite per week in Arlington, VA.
• Candidates should be comfortable attending in-person interviews.
• Local DMV-area candidates are strongly preferred.
• Opportunity to contribute to a high-visibility pilot initiative with potential for extension based on project success.