Senior Data Engineering Specialist (Databricks / Spark)

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Senior Data Engineer

Key Responsibilities

• Design, develop, and operationalize scalable, distributed data pipelines for both batch and real-time processing.
• Collaborate end-to-end with Product Managers and Data Scientists to understand requirements, build prototypes, and deliver production-quality solutions.
• Write clean, high-quality code following engineering best practices and contribute to setting new coding standards as needed.
• Perform peer code reviews to maintain and improve quality across engineering teams.
• Facilitate diagnosis and resolution of technical or functional data issues.
• Advocate for data engineering best practices, process improvements, and developer experience enhancements.
• Build strong relationships across teams and participate in Communities of Practice.
• Engage in continuous learning to stay current with emerging technologies and business domain knowledge.
• Contribute as an active member of an agile engineering team, participating in all aspects of the workflow.

Required Skills & Experience

• 5+ years of experience

  working with big data technologies in enterprise environments.
• Strong expertise in designing and optimizing distributed, scalable, and reliable data pipelines.
• Hands-on experience with

  Databricks

  ,

  Apache Spark

  , and

  Spark Structured Streaming

  for real-time ingestion.
• Proficiency working with

  Kafka

  in event-driven architectures.
• Strong SQL skills and practical experience with cloud data warehouses such as

  Snowflake

  .
• Experience with ETL development, data modeling, performance tuning, and data governance.
• Programming/scripting experience;

  Java exposure is a plus

  .
• Ability to translate business requirements into technical solutions and work effectively in cross-functional teams.