Data Engineer

Important Note (Please Read Before Applying)

🚫 Do NOT apply if:

• You have less than 5 years or more than 10 years of experience

• You lack hands-on AWS & Python experience

• You are on a notice period longer than 30 days

• You are looking for a remote-only position

• You are from a non–data engineering background (e.g., support, testing, BI-only roles)

✅ Apply ONLY if you meet ALL criteria above.

Random or irrelevant applications will not be processed.

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About the Company

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

Data Engineer

Key Responsibilities

• Design, develop, and maintain

  ETL/ELT data pipelines

  using

  Python

  and

  AWS native services

  (Glue, Lambda, EMR, Step Functions, etc.)
• Build and manage

  data lakes and data warehouses

  using

  Amazon S3, Redshift, Athena

  , and

  Lake Formation

• Implement

  data ingestion

  from diverse sources (RDBMS, APIs, streaming data, on-prem systems)
• Optimize data workflows for

  performance, cost, and reliability

  using

  AWS Glue, Athena, Redshift Spectrum

• Develop

  modular Python-based frameworks

  for data ingestion, transformation, and validation
• Work with stakeholders to model data structures and ensure

  data governance and consistency

• Deploy and manage data infrastructure using

  Infrastructure as Code (IaC)

  tools such as

  Terraform

  or

  AWS CloudFormation

• Implement

  data quality monitoring and alerting

  using

  CloudWatch

  ,

  Glue Data Catalog

  , or third-party tools
• Ensure

  data security and compliance

  (IAM roles, encryption, GDPR, masking, etc.)
• Collaborate with

  DevOps and ML teams

  to integrate data pipelines into analytics and AI workflows

Mandatory Skills

Python

AWS services

SQL and NoSQL

data modeling, schema design

Git

data governance, lineage, and cataloging

problem-solving

Preferred / Nice-to-Have Skills

• Experience with

  Apache Spark / PySpark

  on

  AWS EMR

• Exposure to

  Airflow

  ,

  dbt

  , or other orchestration tools
• Knowledge of

  Docker

  ,

  Kubernetes

  , and

  DevOps practices

• Experience with

  machine learning pipelines

  or

  real-time streaming (Kafka, Kinesis)

• Familiarity with

  AWS Glue Studio

  ,

  AWS DataBrew

  , or

  AWS Lake Formation