Job Overview

• Design, build, and maintain scalable data pipelines and curated data assets on Databricks.
• Develop reliable ETL/ELT processes to ingest, transform, validate, and publish data from multiple sources using advanced SQL, Python,PySpark & Dbt.
• Leverage Databricks notebooks, Unity Catalog, job scheduling, and performance optimization tools to ensure efficient and reliable data delivery.
• Create reusable, maintainable, and well-documented pipelines aligned with enterprise data engineering standards.
• Monitor, troubleshoot, and optimize pipeline performance, reliability, and availability of BI-ready datasets.
• Build trusted, reusable datasets, data marts, reporting tables, and views for Power BI, Sigma Computing, and other analytics platforms.

What your background should look like:

• Strong practical experience in data engineering, BI enablement, and analytics delivery.
• Hands-on experience with Databricks data engineering and scalable pipeline development is must.
• Strong proficiency in SQL, Python, and PySpark is must.
• Experience with ETL/ELT design and development across multiple data sources.
• Strong understanding of data modeling, fact and dimension structures, star schemas, and semantic layers.
• Experience building BI-ready datasets, data marts, reporting tables, and reusable data products.
• Strong knowledge of data quality, validation, reconciliation, monitoring, and troubleshooting.

Competencies