Operations Data Engineer

What you'll do

• Design, build, and maintain batch and streaming data pipelines, models, and workflows, with monitoring and data quality controls.
• Partner with analytics, data science, engineering, and platform teams to support production AI/ML workflows and self-service analytics.
• Apply DataOps practices and AI-assisted tools to deliver reliable data products and improve pipeline development.

What they ask for

• Domain expertise in supply chain, operations management, logistics, planning and forecasting, production integration, or channel management.
• Demonstrated expertise building and operating large-scale ETL/ELT pipelines using Python, SQL, and modern frameworks.
• Proficiency with cloud data platforms and open table formats; advanced SQL and experience with workflow orchestration and production data quality, observability, and lineage.
• Experience implementing and productionizing GenAI and Agentic AI tooling, including LLM-assisted code generation, MCP servers, and AI-powered data pipeline automation.

Nice to have

• Experience with data visualization and self-service analytics platforms such as Tableau, Streamlit, or ThoughtSpot.
• Ability to work well in a fast-paced, iterative environment and deliver projects under timeline pressures.

Tools

Python, SQL, dbt, Spark, Kafka/Flink, Snowflake, Delta Lake, Apache Iceberg

AI focus

Operationalize AI/ML workflows and productionize GenAI and Agentic AI tooling, including LLM-assisted code generation, MCP servers, AI-powered pipeline automation, and emerging AI data tools.