Data Engineer

Spectraforce
McLean, VA, United States
12 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Agile Methodology Airflow Amazon Web Services Data Analysis Big Data Data Validation Information Engineering Data Mapping Data Transformation Database Queries Distributed Computing Environment Python (Programming Language)
+6 more
Cloud Services SQL Databases Workflow Management Systems Apache Spark Data Pipelines Databricks

Job description

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., * 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.

Requirements

  • 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., * 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.

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