Senior Data Engineer

As a Senior Data Engineer, you'll architect and build the critical data infrastructure that powers our intelligent platform. You'll own the orchestration layer connecting ad channels, website engagement data, and eCommerce platforms, ensuring data flows seamlessly, context is preserved, and insights drive action.

Responsibilities:

• You'll work across the full data lifecycle from ingestion and transformation to delivery and monitoring while building scalable systems that serve our ML and product teams.
• You'll join an existing data engineering team and collaborate closely with ML engineers, product teams, and customers to build reliable data pipelines that power real business outcomes.
• Your Impact: Build orchestration layers that manage data flows across the eCommerce ecosystem: Maintain context for intelligent summarisation and action; design data models and systems that preserve business context, enabling the right insights at the right time for autonomous agents and human decision-makers.
• Ownend-to-end data engineering solutions using Airflow, Python, and GCP services from design through deployment and monitoring.
• Extend and optimise existing data infrastructure; work with current ingestion tools (Supermetrics) while building custom pipelines where needed.
• Plan and execute future pipeline modernisation; identify opportunities to improve scalability, reliability, and maintainability of existing systems.
• Shape the future of data engineering at Out of the Blue by bringing ideas on automation, optimisation, and best practices.

Requirements:

• 5-8 years of experience building production data pipelines.
• Strong coding skills in Python with expert-level SQL.
• Experience with workflow orchestration using Airflow or similar tools.
• Hands-on experience with GCP (BigQuery, Cloud Storage, Dataflow, Pub/Sub, etc. )
• Understanding of data modelling for analytics and ML use cases.
• Passion for code quality: you write maintainable, well-documented, testable code.

Nice to Have:

• Experience with eCommerce platforms (Shopify, BigCommerce) and their data models.
• Knowledge of adtech/martech ecosystems: tracking pixels, attribution, ad platform APIs.
• Experience with stream processing technologies (Kafka, Pub/Sub, Dataflow).
• Familiarity with agent-based approaches for data orchestration and quality monitoring.
• Understanding of ML pipelines and feature engineering for production ML systems.
• Experience with data quality frameworks and observability tools (Great Expectations, Monte Carlo, etc. )
• Background in reverse ETL and data activation use cases.
• Our values help us make decisions that determine how we achieve our goals.