Data Engineer

Job Title: Data Engineer


Location: Arlington, VA (Hybrid, 3 days onsite/week)


Duration: Long Term Contract

Role:
• Design, develop, test, and operate scalable data-processing solutions using Python, SQL, Spark, Hive, Impala, Databricks, and related technologies.
• Own complex data platform capabilities from ingestion and transformation through publishing and consumption.
• Provide technical leadership for the modernization of on-premises data workloads to Databricks and cloud-based platforms.
• Make and document architecture and design decisions that improve scalability, reliability, maintainability, security, and cost efficiency.
• Build production-ready pipelines with appropriate testing, data-quality controls, observability, operational documentation, and recovery procedures.
• Diagnose and resolve complex performance, reliability, and data-quality issues across distributed systems.
• Contribute directly to implementation while guiding technical execution through design reviews, code reviews, and collaborative problem-solving.
• Reduce technical debt by balancing near-term product delivery with long-term platform sustainability.
• Partner with product managers and data scientists to translate business and analytical requirements into clear, durable technical solutions.
• Mentor engineers, share technical knowledge, and help strengthen engineering practices across geographically distributed teams.
• Evaluate new tools and approaches based on measurable improvements to delivery speed, platform reliability, developer productivity, or analytical capability.
• Participate in production support and continuous improvement of the systems owned by the team.

Ideal Candidate Qualifications:
• Experience modernizing workloads from Hadoop-based environments to cloud or Databricks platforms.
• Experience with Hive, Impala, workflow orchestration, data lakehouse patterns, or cloud object storage.
• Advanced SQL expertise, including query optimization and modeling for very large datasets.
• Knowledge of data governance, privacy, security, data lineage, and access-control practices.
• Experience supporting analytical, economic, financial, or other data-intensive products.
• Experience applying machine learning, generative AI, or agent-based capabilities within production systems.
• Experience mentoring engineers and influencing architecture or engineering standards across teams.
• Excellent verbal and written communication skills, capable of explaining complex technical concepts to diverse audiences.