AWS Data Engineer

3 days ago

Mumbai, Maharashtra, India translab Full time ₹ 6,00,000 - ₹ 18,00,000 per year

Job Title:
AWS

Data

Engineer

Location: Mumbai

Experience Required: 2 to 3 Years

Role Overview:

We are looking for a highly skilled
AWS

Data

Engineer
to join our team. The ideal candidate should have a solid background in SQL, Python, PySpark, and
AWS
. In this role, you will be responsible for designing and developing ETL pipelines and performing
data
migrations using
AWS
DMS and other services such as S3, Lambda, Glue, Step Functions, CloudWatch, and SNS.

Key Responsibilities:

  • Implement 
    data
     migration workflows from Oracle to 
    AWS
     S3 using 
    AWS
     DMS.
  • Design, develop, and maintain 
    data
     ingestion and transformation pipelines using Glue, Lambda, and Step Functions.
  • Develop serverless solutions leveraging 
    AWS
     Lambda for scheduling, automation, and event-driven processing.
  • Manage 
    data
     storage using Amazon S3, including lifecycle policies, versioning, and partitioning.
  • Orchestrate workflows using 
    AWS
     Step Functions for seamless service integration.
  • Monitor and optimize pipeline performance using 
    AWS
     CloudWatch, including alerts and logging.
  • Handle structured and semi-structured 
    data
     formats such as Parquet, Delta, Avro, JSON, and CSV.
  • Work with partitioning strategies on Parquet and Delta formats.
  • Collaborate with 
    Data
     Architects and Analysts on 
    data
     models and schema strategies using 
    AWS
     Glue 
    Data
     Catalog.
  • Ensure 
    data
     quality, security, and compliance across pipelines.
  • Optimize 
    data
     ingestion and transformation for performance and cost efficiency.

Required Skills & Qualifications:

  • Bachelor's degree in Computer Science, IT, or related field.
  • Strong experience with 
    AWS
     
    data
     services – S3, Glue, Lambda, Step Functions, DMS, CloudWatch, SNS, etc.
  • Hands-on experience with Python / PySpark for 
    data
     transformation.
  • Solid understanding of 
    data
     warehousing concepts and ETL/ELT processes.
  • Proficiency in SQL (Amazon Redshift, PostgreSQL, Oracle, or similar).
  • Experience building event-driven and serverless architectures.
  • Familiarity with 
    data
     lake and 
    data
     catalog implementations (Glue 
    Data
     Catalog).
  • Experience in performance tuning and parallel processing on 
    AWS
    .
  • Strong analytical and problem-solving abilities.
  • Excellent communication and team collaboration skills.
  • Ability to work effectively in a fast-paced and dynamic environment.

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