Job description

Description

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

Requirements

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.