Databricks + Pyspark

AIA - Coimbatore

Experience : 6 to 9 years

Job Summary

Serve as a senior developer specializing in Databricks and PySpark to design build and optimize large scale data and analytics solutions in a hybrid work environment using prompt engineering to enable intelligent data products supporting day shift operations without travel and delivering measurable value to business stakeholders and society through data driven outcomes.

Responsibilities

• Design and develop scalable data pipelines on Databricks using PySpark and Databricks SQL to deliver reliable and timely data for analytics and reporting needs.
• Implement robust data transformation logic in Databricks Workflows to ensure consistent data quality and alignment with business rules across multiple domains.
• Configure and optimize Databricks CLI based automation scripts to streamline environment setup deployment and operational tasks for data engineering projects.
• Apply prompt engineering techniques to build and refine intelligent data solutions that improve insight discovery and decision support for business teams.
• Tune PySpark jobs and Databricks SQL queries to improve performance manage costs and ensure efficient use of compute resources across the data platform.
• Collaborate with data architects analysts and product teams in a hybrid work setup to translate complex requirements into clear maintainable Databricks based solutions.
• Establish monitoring logging and alerting practices for Databricks Workflows to ensure high reliability rapid incident detection and swift remediation.
• Document data models transformation logic and operational runbooks so that project teams can understand support and extend delivered solutions with confidence.
• Ensure all data solutions comply with security and privacy standards so that sensitive information is protected while enabling responsible insight generation.
• Mentor junior developers in Databricks PySpark and prompt engineering techniques so that the team continually improves its technical depth and delivery quality.
• Partner with business stakeholders to validate outputs from Databricks SQL dashboards and models so that delivered insights remain accurate relevant and actionable.
• Drive continuous improvement of development practices using Databricks CLI and version control so that releases remain predictable traceable and low risk.
• Contribute to innovative use cases that leverage Databricks and prompt engineering to generate positive business value and broader societal impact through better use of data.