Software Engineer - Data Integration

Contribute to data pipelines for ingestion, transformation, and distribution of datasets, implementing features that require analysis across a variety of factors.

Build ETL/ELT workflows using distributed computing frameworks on cloud infrastructure, applying team standards and adapting approaches where needed.

Implement and test API endpoints that expose ingestion, processing, and distribution capabilities, with a focus on correctness and clear contracts.

Write automated tests and contribute to data quality validation and monitoring for pipeline components you work on.

Apply Samba's platform patterns to produce reliable, maintainable code that fits within the broader system.

Implement partner and destination integrations against established patterns.

Apply privacy and data governance requirements (GDPR, CCPA) to the code you write, following established team patterns and escalating questions appropriately.

Collaborate closely with your immediate team and reason about how your work fits within the broader data platform.

Participate in code reviews, both as an author and a reviewer.

Write clear, well-tested, maintainable code that meets the team's quality standards.

Communicate proactively about blockers, progress, and questions, and engage constructively in team discussions.

Participate in on-call rotations and contribute to improving operational practices across the team.

Implement monitoring and alerting for components you own.

Help maintain and improve CI/CD pipelines and testing coverage for team systems.

2+ years of professional software engineering experience with a Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or an advanced degree without prior experience, or equivalent), with experience in data engineering, backend systems, or distributed data infrastructure.

Proficiency in Python and SQL; ability to write clean, tested, production-ready code.

Hands-on experience with AWS or GCP and their core data services.

Experience with data pipeline tools or workflow orchestration (e.g., Airflow, dbt, or equivalent) in a production environment.

Familiarity data privacy regulations (GDPR, CCPA).

Ability to communicate clearly, ask good questions, and work collaboratively within a team.

Exposure to distributed processing frameworks (e.g., Spark, Databricks, or equivalent).

Familiarity with streaming or event-driven data systems (e.g., Kafka or equivalent).

Exposure to ad tech, audience activation, data licensing, or digital media.