Data Engineer

Job Title: Data Engineer
Location: Mclean, VA (Hybrid)
Duration: 5+ Months

Interview Process: Technical coding interview

Position Overview
We are seeking an experienced Senior Data Engineer to support Discover Loan Integration initiatives. The ideal candidate will have strong hands-on experience building, testing, and supporting data pipelines using Python, Apache Spark, AWS, SQL, and Airflow.
This role involves working within small, collaborative engineering pods to integrate source data into a new platform, understand data requirements, perform data mapping and validation, and develop reliable batch data pipelines. The candidate will participate in discovery activities, collaborate with cross-functional teams, and provide ongoing production support.
Key Responsibilities

• Design, develop, test, and maintain scalable data pipelines for Discover Loan Integration.
• Build and support batch data processing workflows using Python, Apache Spark, AWS, and SQL.
• Develop and orchestrate data workflows using Apache Airflow.
• Analyze source data, understand business requirements, and perform source-to-target data mapping.
• Use Databricks to connect to source systems, explore data, validate mappings, and establish baseline outputs.
• Write SQL queries to extract, transform, validate, and reconcile data.
• Identify data quality issues, investigate discrepancies, and ensure the accuracy and consistency of pipeline outputs.
• Support pipeline deployment, troubleshooting, and ongoing production operations.
• Collaborate with engineers and stakeholders in small, agile engineering pods to deliver integration initiatives.
• Participate in technical problem-solving, testing, and continuous process improvement.

Required Skills

• Strong hands-on experience with Python programming.
• Experience developing data pipelines using Apache Spark.
• Practical experience with AWS cloud services for data engineering.
• Strong SQL skills, including querying, data validation, and data analysis.
• Experience with Apache Airflow for workflow orchestration and scheduling.
• Hands-on experience building, testing, and supporting batch data pipelines.
• Strong understanding of data mapping, data transformation, source-to-target reconciliation, and data validation.
• Ability to analyze complex datasets, troubleshoot issues, and work independently.

Preferred Qualifications

• Experience with Databricks and distributed data processing.
• Previous experience in data engineering, data analysis, or production support.
• Experience developing APIs to expose or serve data.
• Experience working in Agile teams or small engineering pods.
• Strong analytical, problem-solving, and communication skills.