6 months contract.

Our partner is looking for a Senior Data Engineer to build and operate the data pipelines that power our machine learning recommendation systems. The data you deliver directly drives ML models that generate promotion and pricing recommendations for business users across the company—helping them make faster, smarter, data-driven decisions.

You'll work at the intersection of data engineering and machine learning, building reliable, production-grade pipelines in Google Cloud Platform. Source data lives in BigQuery and the curated, model-ready tables you produce land back in BigQuery, so you will own the full flow from raw source to ML-ready feature tables.

• Design, build, and maintain scalable data pipelines that feed ML models producing promotion and pricing recommendations.

• Orchestrate complex, dependency-aware workflows using Apache Airflow.

• Transform and model source data in BigQuery into clean, well-documented, model-ready tables.

• Partner with data scientists and ML engineers to understand feature requirements and deliver reliable, timely datasets.

• Ensure data quality, reliability, and observability across pipelines through testing, monitoring, and alerting.

• Optimize BigQuery queries and pipeline performance for cost and speed.

• Collaborate with business stakeholders to translate promotion and pricing needs into data requirements.

• Contribute to engineering best practices, code reviews, and technical design decisions.

• 5+ years of experience in data engineering or a comparable role.

• Strong hands-on experience with Apache Airflow for workflow orchestration.

• Deep expertise in Google Cloud Platform (GCP).

• Advanced SQL and proven experience building data models and pipelines in BigQuery.

• Solid understanding of machine learning concepts and how data pipelines support ML models (feature engineering, training data, model inputs/outputs).

• Strong programming skills (e.g., Python).

• Experience building production-grade, reliable pipelines with an eye for data quality and observability.

Nice to Have

• Hands-on experience with GCP Vertex AI.

• Experience supporting ML/recommendation systems in production.

• Familiarity with pricing, promotions, or retail/e-commerce domains.

• Experience with CI/CD, infrastructure-as-code, and data pipeline testing frameworks.