BI Engineer: Cloud Data Pipelines & Self-Service Analytics

Village Super Market; New York (NY); On-site; USD 110,000 - 170,000; Full time

Job summary

Village Super Market seeks a Business Intelligence (BI) Engineer to design, build, and run scalable data pipelines. You will transform data from SAP ERP and other systems into analytics-ready datasets in Google BigQuery, enabling trusted reporting and analytics for NY Fairway & GG leadership.

The role emphasizes ELT/ETL workflow development in Python and SQL, data modeling, and enabling self-service analytics with ThoughtSpot and BI tools. Collaboration with cross-functional teams is essential.

Qualifications

• Bachelor’s degree or equivalent professional experience in a relevant field.
• 5+ years in BI development or data engineering.
• Strong SQL and Python development skills.
• Experience with cloud data engineering and data warehousing.

Responsibilities

• Design, build, and maintain data pipelines from SAP ERP and other sources into Google Cloud.
• Develop ELT/ETL workflows using Python and SQL for analytics-ready datasets.
• Create and optimize BigQuery data models and semantic structures for BI tools.
• Support self-service analytics and reporting with ThoughtSpot and other BI platforms.
• Collaborate with Retail, Merchandising, Finance, and IT to translate business needs into data solutions.
• Automate data workflows using GCP services like BigQuery Scheduler and Cloud Composer.
• Ensure data quality, governance, and maintain documentation.

Skills

SQL

Python

Communication

Collaboration

Education

Bachelor’s degree or equivalent

Tools

BigQuery

Google Cloud Storage

ThoughtSpot

Tableau

Power BI

Job description

Village Super Market seeks a Business Intelligence (BI) Engineer to design, build, and run scalable data pipelines. You will transform data from SAP ERP and other systems into analytics-ready datasets in Google BigQuery, enabling trusted reporting and analytics for NY Fairway & GG leadership.

The role emphasizes ELT/ETL workflow development in Python and SQL, data modeling, and enabling self-service analytics with ThoughtSpot and BI tools. Collaboration with cross-functional teams is essential.