Job Title: Senior Data Engineer Databricks
Experience: 6 10 Years
Work Mode: Hybrid
Shift Timing: 4:00 PM 1:00 AM IST Role Overview
We are looking for an experienced Senior Data Engineer with strong hands-on exposure to Databricks to design, build, and optimize scalable data pipelines and analytics platforms. The role involves working closely with cross-functional teams to support data-driven decision making in a hybrid work environment. Key Responsibilities
Design, develop, and maintain scalable data pipelines using Databricks.
Build and optimize ETL/ELT workflows for structured and unstructured data.
Develop data transformations using PySpark / Spark SQL.
Ensure data quality, reliability, and performance across pipelines.
Work with large-scale datasets and implement best practices for data modeling.
Collaborate with data scientists, analysts, and stakeholders.
Monitor and troubleshoot data workflows and production issues.
Participate in code reviews, performance tuning, and optimization.
Support deployments and maintenance during the evening shift (4 PM 1 AM). Mandatory Skills
Strong hands-on experience with Databricks.
Expertise in Apache Spark (PySpark / Spark SQL).
Solid experience in building data pipelines and data lakes.
Strong SQL skills and experience with data modeling.
Experience with cloud platforms (AWS / Azure / GCP).
Knowledge of workflow orchestration tools (Airflow, ADF, etc.).
Strong debugging and performance tuning skills. Good to Have
Experience with Delta Lake and Databricks optimization techniques.
Exposure to real-time or streaming data processing.
Experience working with large-scale enterprise data platforms.
Knowledge of CI/CD for data pipelines.
Understanding of data governance and security best practices. Soft Skills
Strong problem-solving and analytical skills.
Good communication and stakeholder management.
Ability to work independently in a fast-paced environment.
Mentoring junior engineers. Education
BE / BTech / MCA / MSc in Computer Science, Data Engineering, or related field.
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