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AWS Databricks Spark Scala Jar Developer

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Onsite

AWS Databricks Spark Scala Jar Developer

Tata Consultancy Services

AWS Databricks Spark Scala Jar Developer

Skills

SQL QueriesDockerPythonKafkaSnowflakeAmazon RedshiftDatabricksScalaAWSKubernetesPySparkApache AirflowComplianceTerraform

23 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

28 September 2026

What they need


TCS Hiring for AWS Databricks Spark Scala Jar Developer

Experience Range: - 07 To 10 Years (Mandatory)

(Note: Candidates below 7 years of IT experience shall not be considered)

JOB LOCATION: Bengaluru, Hyderabad

JOB DESCRIPTION

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

Minimum Qualification:

15 years of Full Time Education

Interested candidates kindly share your updated resume to [email protected] along with filling the following details to maximize your chances of getting calls from TCS. The details are as follows:

Section 1: Basic Details:

  • Candidate Name:
  • Email ID:
  • Phone Number:
  • Current Location (City):
  • Preferred Location (City):

Section 2: Educational Details:

  • Highest Regular Full‑Time Qualification
  • (Diploma / Graduation / Post Graduation / Others)
  • 10th Completion Year
  • 12th / Intermediate Completion Year
  • Graduation Completion Year
  • Post‑Graduation Completion Year (if applicable)

Section 3: Work Experience:

  • Current Company Name
  • Total Experience (in years)
  • Number of Companies Worked
  • Employment Timeline
  • (Example: Company A – 2021 to Present, Company B – 2019 to 2021)

Section 4: Compensation Details:

  • Current CTC (in LPA)
  • Expected CTC (in LPA)
  • Notice Period
  • (Immediate / 15 Days / 30 Days / 60+ Days)

Section 5: Documentation & Compliance (Yes / No):

  • Valid ID Proof Available (Aadhar & Pan Card): (Yes/No)
  • Educational Documents Available: (Yes/No)
  • Employment Documents Available: (Yes/No)
  • UAN Number Available: (Yes/No)

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