Senior Databricks Data Engineer

• Must Have Technical/Functional Skills
• 8+ years of experience in Data Engineering, ETL/ELT, and Data Warehousing.
• 5+ years of hands-on experience with Databricks, PySpark, and Apache Spark.
• Strong expertise in Delta Lake, Lakehouse Architecture, and large-scale data processing.
• Advanced SQL and PL/SQL development skills.
• Experience designing and implementing scalable batch and real-time data pipelines.
• Strong knowledge of dimensional, relational, and analytical data modeling.
• Experience with Spark SQL, DataFrames, Hive, and distributed computing frameworks.
• Hands-on experience with AWS services, including S3, IAM, Glue, Lambda, and Redshift.
• Strong understanding of Databricks-AWS integrations and cloud-native architectures.
• Experience with data quality, performance tuning, optimization, and troubleshooting.
• Knowledge of CI/CD, Git, DevOps practices, and deployment automation.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Prior experience leading technical teams and mentoring junior engineers.
• Roles & Responsibilities
• Gather and analyze business and technical requirements from stakeholders and clients.
• Design end-to-end data solutions, architectures, and scalable data models.
• Develop and optimize data ingestion, transformation, and analytics pipelines using Databricks and PySpark.
• Create and maintain conceptual, logical, and physical data models.
• Lead solution design activities, including High-Level and Low-Level Design documentation.
• Implement data quality, monitoring, governance, and performance optimization best practices.
• Collaborate with Product Owners, Architects, and Business Analysts to define project scope and delivery plans.
• Provide technical leadership, mentoring, and guidance to onshore and offshore teams.
• Conduct design reviews, code reviews, and troubleshooting sessions to ensure solution quality.

None flagged.