Data Engineer

Roles & Responsibilities:-Develop and Optimize Data Pipelines using PySpark and SQL in Databricks to handle large-scale data transformations and batch/streaming workloads.

-Design and Implement ETL Processes by leveraging Databricks notebooks, Delta Lake, and Python-based custom scripts for data ingestion and curation.

-Collaborate with Data Analysts and Stakeholders to understand data needs and deliver accurate, performant, and reusable data solutions.

-Maintain and Monitor Job Performance, identify bottlenecks, and apply tuning techniques to improve pipeline efficiency on the Databricks platform.Professional & Technical Skills

:-Proficient in building scalable, distributed data pipelines using PySpark and Databricks with a deep understanding DataFrame APIs, and Spark optimization techniques

.-Experience on Python for scripting, data manipulation, and integrating third-party libraries within data engineering workflows

.-Expertise in SQL for data extraction, transformation, complex joins, and performance tuning across relational and distributed data stores.

-Experienced in working with Delta Lake, versioned data, schema evolution, and managing CDC (Change Data Capture) scenarios in a cloud-based environment.

-Best practices in CI/CD, code versioning (Git), and DevOps for data projects.Additional Information.