Data Engineer
Core
Design, develop, and support scalable data pipelines and ETL/ELT processes that power analytics and machine learning work; build data architectures and deploy ML models for forecasting, classification, and optimization.
Role type
Senior Data Engineer (ML-enabled)
Builds
Scalable data pipelines, data architectures, and deployed machine learning models
Domain
Data Engineering, Machine Learning, Cloud Infrastructure
Required skills
Python, SQL, data pipeline design, large-scale dataset handling, cloud environment management (AWS/Azure/GCP), data visualization, analytical problem-solving
Preferred skills
Containerization and orchestration (Docker, Kubernetes), data warehousing (Snowflake, Redshift, BigQuery), MLOps practices, Agile/Scrum methodologies
Technologies
Airflow, AWS, Redshift, Azure, BigQuery, Docker, Kubernetes, Power BI, PyTorch, SQL, Snowflake, Spark, Tableau, TensorFlow
Responsibilities
Design and develop scalable data pipelines and ETL/ELT processes; build and refine data architectures in cloud and on-premises environments; examine complex data sources to uncover insights; develop, train, and deploy machine learning models; partner with product, engineering, and business teams to translate requirements into technical solutions; maintain data accuracy, consistency, and governance; create dashboards and reports using BI tools; evaluate data workflows and recommend improvements
Seniority
Senior, hands-on IC