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Data Migration Developer

Techtrinite Consulting

Hyderabad, Telangana, India · 계약

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경험
4~8세
샐러리
INR 1,300,000 – INR 1,800,000 / year
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1
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2시간 전
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적임
Any graduate may apply. The role is intended for candidates with data engineering experience, especially those who have handled cloud data platform migrations and Databricks-based modernization projects.
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Role Overview

This position is for a data migration specialist who will help modernize enterprise data platforms by moving workloads from Amazon Redshift and AWS Glue into Databricks. The role focuses on rebuilding and improving ETL/ELT processes, protecting data quality, and ensuring the migrated solution performs reliably at scale.

Key Responsibilities

  • Review existing data pipelines, ETL processes, and warehouse objects currently running in Amazon Redshift and AWS Glue.
  • Plan and execute migration approaches for transferring data and workloads to Databricks.
  • Build, tune, and support ETL/ELT pipelines using Databricks, Apache Spark, and Python.
  • Rework SQL scripts, stored procedures, and transformation logic so they function effectively in Databricks-based solutions.
  • Check data accuracy, completeness, and consistency before migration and after cutover.
  • Improve Databricks data models, partitioning strategy, and overall processing performance.
  • Apply Delta Lake practices for storage efficiency, version control, and optimization.
  • Work closely with architects and business stakeholders to ensure the solution aligns with requirements.
  • Investigate migration issues and resolve performance bottlenecks.
  • Prepare technical documentation, migration playbooks, and handover material.
  • Maintain compliance with security, governance, and regulatory standards during the migration process.

Requirements

  • A bachelor’s degree in Computer Science, Information Technology, Engineering, or a similar discipline.
  • At least 4 years of experience in data engineering or data platform migration work.
  • Practical expertise with Amazon Redshift, AWS Glue, Databricks, Apache Spark, Python, and SQL.
  • Working knowledge of cloud environments, ideally AWS.
  • Strong understanding of data warehousing principles and dimensional modeling.
  • Hands-on experience with Delta Lake and Lakehouse architecture.
  • Exposure to ETL/ELT frameworks and workflow orchestration tools.
  • Experience using Git and CI/CD pipelines.
  • Good analytical thinking and troubleshooting ability.
  • Strong written and verbal communication skills, including documentation.
  • Preferred exposure to Databricks Workflows, Unity Catalog, and Delta Live Tables.
  • Familiarity with Apache Airflow or similar orchestration tools is an advantage.
  • Experience with Infrastructure as Code tools such as Terraform or CloudFormation is a plus.
  • AWS and/or Databricks certifications are beneficial.
  • Background in large-scale enterprise data migrations is preferred.
  • Minimum overall experience required: 4 to 8 years in data engineering.
  • Relevant migration experience required: at least 2 years moving cloud data platforms to Databricks.

Technical Focus

  • Cloud platform: AWS
  • Data warehouse: Amazon Redshift
  • ETL tool: AWS Glue
  • Target platform: Databricks
  • Programming languages: Python and SQL
  • Processing frameworks: Apache Spark and PySpark
  • Storage layer: Delta Lake
  • Version control: Git
  • CI/CD tools: Azure DevOps, GitHub Actions, or Jenkins

Success Measures

  • Move Redshift databases and AWS Glue ETL jobs successfully into Databricks.
  • Deliver accurate reconciliations with very low data mismatch rates.
  • Improve performance and scalability of pipelines on the Databricks Lakehouse platform.
  • Provide complete migration documentation and support a smooth operational transition.
  • Finish the migration within the planned schedule while keeping business disruption to a minimum.

Employment Details

This is a full-time or contract opportunity depending on project needs.

The position is based in Hyderabad, India.

Additional Information

This opportunity is best suited to a data engineer who has worked on cloud data migrations and modernized enterprise platforms using Databricks.

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