We are looking for seasoned Senior Data Engineer to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines. We are looking for more than just a "Senior Data Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.
- Lead and architect migration of data environments with performance and reliability.
- Assess and understand the ETL jobs, workflows, BI tools, and reports
- Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products
- Experience in crafting database / data warehouse solutions in Databricks
- Key must have skill sets – Databricks, Python, SQL
- Support an Agile software development lifecycle
- You will contribute to the growth of our Data Exploitation Practice!
• Ability to hold a position of public trust with the US government.
• 12+ years of experience with a Bachelors Degree or 8+ years with a Masters Degree.
• 8-12 years industry experience in data engineering and a passion for solving complex problems.
• 8-12 years direct experience in Data Engineering with experience in the following:
- Experience designing and building data pipelines and data products on modern lakehouse platforms (e.g. Databricks, Apache Spark), including Delta Lake, distributed processing and performance optimization.
- Experience supporting or integrating GenAI/ML workflows (e.g. feature engineering, vectors torage, RAW pipelines, or model lifecycle using tools like MLFlow)
- Experience operating in enterprise or regulated cloud environments, including working within platform constraints, security controls, and data governance frameworks.
- Experience building batch and streaming data pipelines using distributed processing frameworks (e.g. Apache Spark Structured Streaming) within a lakehouse architecture.
- Experience with search and retrieval patterns for analytics or AI use cases (e.g. indexing, semantic search, vector-based retrieval)
- Strong proficiency in SQL and Python for data engineering, including experience working with distributed data processing frameworks (e.g. Apache Spark)
- Advanced working SQL knowledge and experience working with relational databases, query authoring and optimization (SQL) as well as working familiarity with a variety of databases.
- Strong ability to lead technical discussions with both technical and non-technical stakeholders, including translating business needs into actionable data solutions, clearly communicating tradeoffs, and guiding decision-making
- Demonstrated ability to evaluate solution feasibility, identify risks and constraints, and make pragmatic recommendations in complex or ambiguous environments.
- Experience navigating cross-team environments and driving alignment through clear communication and structured problem-solving
- Experience constructing complex queries to analyze results using databases or in a data processing development environment
- Strong judgment in evaluating solution feasibility, balancing technical constraints, business needs, and long-term scalability
- Experience architecting data systems (transactional and warehouses)
- Experience aggregating results and/or compiling information for reporting from multiple datasets
- Experience working in an Agile environment
- Experience supporting project teams of developers and data scientists who build web-based interfaces, dashboards, reports, and analytics/machine learning models