Data Engineer
Core
Design and run reliable data pipelines at scale, architect data platforms (warehouses, lakes, lakehouses), and build feature-store infrastructure to serve clean, documented data for data scientists and AI engineers.
Role type
Senior Data Engineer (MLOps focus)
Builds
Scalable batch and streaming data pipelines, data platforms, and feature stores
Domain
AI/ML infrastructure, Data Engineering
Deliverable
production ML models
Required skills
Python, PySpark, SQL, Data Modeling, Data Governance, Pipeline Orchestration, Cloud Platforms (AWS/GCP/Azure), Containerization, Systems Thinking
Preferred skills
Graph Data (Neo4j), MLOps practices, Feature Store architecture
Technologies
Python, Postgres, MongoDB, Neo4j, PySpark, HDFS, Airflow, Databricks, AWS, GCP, Azure
Responsibilities
Design and maintain scalable data pipelines; Architect data platforms and graph data foundations; Ensure data quality, governance, and lineage; Build reusable feature-store infrastructure; Define clear data contracts for downstream consumers.
Seniority
Senior, hands-on IC
