The Data & Software Engineer works with a small team to build complex data flows for a custom application. Successful candidate will have advanced Python programming skills, familiarity with Java, an understanding of data security, privacy, governance and compliance principles and a demonstrated history of building production data pipelines and ETL workflows at scale. Candidate must have experience:

• Building end-to-end data pipelines leveraging Python Using orchestration tools to deploy data pipelines, including configuring and updating Spark Jobs
• Containerizing and deploying applications in cloud environments like AWS.
• Working with MySQL and PostgreSQL including performance tuning, schema design, and query optimization for complex, analytical workloads. 
• Leveraging industry standard tools for code control (Git, IaaC control, etc.)
• Working with data catalogs, tracking data lineage  and handling a variety of data formats, including Geospatial.
• Using Bash scripting for automation and data processing tasks
• Integrating Al/ML services and models 

*This role requires an active TS/SCI FSP to start*

Required Skills:

Minimum of 5 years' experience with: 

·  Apache Spark & PySpark

·  Advanced Python skills (including Pandas & NumPy)

·  Docker, Podman

·  AWS S3, Lambda & Step functions

·  Apache Iceberg, Airflow, etc.

·  SQL (with Trino)

·  NoSQL, DynamoDB

·  Unity Catalog OSS, Apache Polaris

·  Apache Superset

·  Terraform or CloudFormation

·  OpenLineage

·  H3, PostGIS

Responsibilities:

• Work with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight
• Leverage strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks
• Leverage a background in large-scale data migration or platform modernization efforts
• Contribute to data engineering documentation, best practices, and design patterns.