Data Engineer IILocation: Arlington, VA (Hybrid - 3 Days Onsite)
Duration: Through September 2026 with potential extension
Interview Process: In-Person Interviews
Industry: Financial Services / Payments
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.
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.
Responsibilities- 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.
Required Qualifications- 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.
Preferred Qualifications- 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.
Additional Information- 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.
Keywords: Data Engineer, Spark, PySpark, Hadoop, HDFS, Hive, Ozone, Python, SQL, ETL, Data Pipeline, Data Warehouse, Big Data, Analytics, Financial Services, Payments, Arlington VA.
