AWS Databricks Spark Scala Jar Developer

Key Responsibilities:

• Design and develop scalable data-processing applications using Apache Spark and Scala.
• Develop reusable frameworks, utilities, and libraries and package them as JAR files.
• Deploy and execute Scala-based JAR applications on AWS Databricks clusters.
• Build and maintain high-volume batch and streaming data pipelines.
• Develop ETL and ELT workflows using Databricks, Spark, Scala, and SQL.
• Integrate Databricks with AWS services such as S3, Glue, IAM, Secrets Manager, CloudWatch, and Redshift.
• Implement data ingestion and transformation solutions for structured, semi-structured, and unstructured data.
• Perform Spark performance tuning, including partitioning, caching, join optimization, and memory management.
• Develop and maintain Delta Lake tables and data-processing workflows.
• Configure Databricks jobs, workflows, clusters, libraries, and access controls.
• Implement error handling, logging, auditing, monitoring, and restart mechanisms.
• Write unit and integration tests for Scala and Spark applications.
• Build CI/CD pipelines to automate JAR creation, testing, and deployment.
• Troubleshoot data pipeline failures, cluster issues, and production defects.
• Participate in solution design, code reviews, release planning, and production support.
• Collaborate with data architects, analysts, DevOps teams, and business stakeholders.

Desired Candidate Profile:

• Strong hands-on coding experience in Scala and Apache Spark.
• Proven experience in developing and deploying Scala-based JAR applications.
• Strong understanding of Spark architecture, distributed computing, and performance tuning.
• Experience in building enterprise-scale data pipelines using AWS Databricks.
• Good understanding of data lake, data warehouse, and Delta Lake concepts.
• Ability to troubleshoot complex production issues independently.
• Strong analytical, debugging, and problem-solving skills.
• Good communication and stakeholder-management capabilities.
• Experience working in Agile or Scrum delivery environments

Preferred Skills:

• Spark Structured Streaming
• Apache Kafka
• Python or PySpark
• AWS Lake Formation
• Terraform or CloudFormation
• Apache Airflow
• Snowflake
• Data warehouse and data lake architecture
• Databricks Asset Bundles
• Docker and Kubernetes
• Experience with BFSI or other regulated domains
• AWS or Databricks certification