DataBricks – Technical Lead (Exp: 8 Yrs to 12 Yrs)
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Job Description
Structured overview of role & requirementsAbout This Role
Design and deliver scalable, high-performance data pipelines and Lakehouse workflows using Databricks, PySpark, and Spark SQL on cloud platforms (Azure/AWS).
Lead development teams by mentoring engineers, performing code reviews, and enforcing best practices in data engineering.
Collaborate with product owners, business analysts, and architects to translate business requirements into technical solutions and manage production workload performance.
Minimum Requirements
8 to 12 years of IT experience with at least 3 years on big data and Databricks.
Strong hands-on skills with Databricks, PySpark, Spark SQL, and cloud data lakes (Azure ADLS, AWS S3).
Experience with Azure Data Factory or AWS Glue, relational databases, Delta Lake, Unity Catalog, streaming data (Kafka/Event Hubs), Infrastructure-as-Code (Terraform).
Bachelor's or Master's degree in Computer Science, Engineering, or related field; Databricks Certified Data Engineer Professional; and Microsoft DP-700 or AWS Data Engineer Associate certification.
Ideal Candidate Profile
Experienced technical lead with proven ability to design and deliver complex data engineering solutions in agile environments.
Hands-on expert in Databricks platform and related big data technologies with practical knowledge of operationalizing data pipelines on cloud ecosystems.
Strong mentor and team leader capable of guiding engineers, reviewing code, and maintaining engineering standards while collaborating cross-functionally.