Analysis Skills, Apache Hadoop, Apache Hive, Apache Spark, Automation, Banking Services, Coding Standards, Communication Skills, Continuous Improvement, Customer Relations, Customer Support/Service, Data Analysis, Data Management, Data Modeling, Data Processing, Data Quality, Data Sets, Data Warehousing, Database Extract Transform and Load (ETL), Ecosystems, Financial Services, HDFS (Hadoop Distributed File System), Identify Issues, Problem Solving Skills, Process Improvement, Python Programming/Scripting Language, SQL (Structured Query Language), Scalable System Development, Source Code/Configuration Management (SCM), Transaction Processing/Management
Data Engineer II
Location: Arlington, VA (Hybrid – 3 Days Onsite)
Duration: Through September 2026 with potential extension
Interview Process: In-Person Interviews
Industry: Financial Services / Payments
About the Role
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.