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Sr. Data Analytics Engineer
Skills
Warehouse OperationsApache AirflowContextData AnalyticsData IntegrityData WarehousingDatabases
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 6+ years experience in data or software-adjacent field at scale
- Experience designing and implementing mature data pipelines across a data lake and EDW
- Experience with Dimensional Kimball modeling methodologies
- Experience integrating fragmented or disparate source systems into reliable data products
- Experience with ELT ETL tooling and workflow orchestration such as Apache Airflow
- Strong SQL skills in an analytical context
- Experience with relational databases
- Experience with data exploration visualization and storytelling
- Excellent written and spoken communication skills
- Ability to write and maintain high-quality reusable code
- Track record owning complex ambiguous data initiatives end to end
- Experience with Snowflake Airflow and Tableau is preferred
Nice to have
- Pragmatic AI adopter
- Strong ownership
- Cross-functional collaborator
- Analytical thinker
- Process oriented
Day to day
- Design and build scalable data models and pipelines for supply chain and merchandise planning teams
- Integrate logistics visibility planning ERP and PLM data into Snowflake for inventory transit freight and landed cost insights
- Lead technical design establish engineering standards and deliver trusted reusable analytics data products end to end
- Own data quality monitoring governance and validation for critical upstream feeds and enterprise data warehouse models
- Translate complex operational data into clear actionable insights for both technical and non-technical stakeholders
Hiring process
- Submit application
- Interviews via phone in person Teams or Zoom
- Verbal offer followed by written confirmation