Data & Software Engineer

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

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.

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