Description

You will architect, build, and optimize data-lakehouse solutions on Databricks for enterprise clients.

Responsibilities

• Design and implement end-to-end ETL/ELT workflows using Java, Scala, and Spark for both batch and streaming.
• Tune performance using Spark UI metrics, AQE, and partitioning to scale to multi-TB datasets.
• Configure Delta Lake features including OPTIMIZE, Z-Ordering, time travel, and Unity Catalog.
• Lead discovery sessions, deliver PoCs, and translate business requirements into technical solutions.
• Triage and resolve production issues such as data skew, executor failures, and memory errors.

Required Skills

• 5+ years of experience with Apache Spark (DataFrame, SQL, and RDD) at scale.
• 5+ years of experience with Databricks (Jobs, Workflows, and Unity Catalog).
• 4+ years of experience with Java including Spring and Maven or Gradle.
• Proficiency in Scala and Apache Spark.
• Mandatory Databricks Certified Professional Data Engineer certification.
• Expertise in Spark internals and performance tuning.
• Experience managing large-scale datasets and ensuring SLA adherence.

Key Skills

Education

Any Graduate