Job Description:

- 8+ yrs of experience in data engineering with 23 yrs in a lead or architect role.

- Experience in Microsoft Fabric, ADF, DWH, Databricks, PySpark, Snowflake, and Power BI.

- Strong in SQL and Python/Scala.

- Experience with Azure, AWS, and GCP.

- Notice Period: Immediate.

Key Responsibilities :

- Architect and deploy end-to-end data pipelines using Azure Data Factory and Spark to streamline data ingestion and transformation for enterprise-level reporting.

- Design and maintain high-performance Lakehouse architectures utilizing Delta Lake and Azure Data Lake Storage to ensure data integrity and accessibility.

- Lead the migration and optimization of legacy data warehouses into modern Fabric-based environments to enhance query performance and reduce operational latency.

- Implement MLOps best practices by integrating ML Flow into data workflows, enabling seamless model deployment and lifecycle management for data science teams.

- Mentor junior engineers and conduct rigorous code reviews to maintain high standards of software engineering and data quality across all projects.

- Partner with business stakeholders to identify data bottlenecks and implement automated solutions that improve overall data throughput and reliability.