Role & responsibilities

About the Role

Hudson Data is seeking a Data Engineer with solid expertise in Python, SQL, GCP, and BigQuery to build scalable data platforms that power analytics, machine learning, and AI-driven products.

You will design reliable ETL/ELT pipelines, develop cloud-based data models, and work closely with data scientists, analysts, and product teams to make high-quality data available for advanced analytics and AI use cases.

Key Responsibilities
- Design and maintain scalable ETL/ELT pipelines using Python, SQL, and GCP services.
- Build optimized data models and analytics-ready datasets in BigQuery.
- Integrate data from APIs, databases, files, and third-party platforms.
- Support AI and machine-learning workflows through reliable feature and training datasets.
- Implement data-quality checks, reconciliation, monitoring, logging, and error handling.
- Optimize SQL queries, pipeline performance, and BigQuery cost efficiency.
- Orchestrate batch and near-real-time workflows using Airflow or Cloud Composer.
- Maintain data governance, security, lineage,



and access controls.
- Collaborate with data scientists, analysts, engineers, and business stakeholders.

Required Skills
- Strong hands-on experience with Python for data processing and automation.
- Advanced SQL, including complex joins, window functions, CTEs, query optimization, and performance tuning.
- Strong experience with Google Cloud Platform.
- Hands-on expertise in BigQuery, including data modeling, partitioning, clustering, and cost optimization.
- Experience building production-grade ETL/ELT pipelines.
- Familiarity with Airflow or Cloud Composer.
- Understanding of data warehousing, star schema, and dimensional modeling.
- Experience handling large datasets and implementing data-quality controls.
- Working knowledge of Linux/Unix and Git.

AI-Oriented Experience
- Experience preparing datasets for machine learning and generative AI applications.
- Familiarity with feature engin

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🏢 Hudson Data
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