AWS Data Engineer

Important Note (Please Read Before Applying)

🚫 Do NOT apply if:

• You have less than 5 years or more than 10 years of total data engineering experience
• You do not have strong AWS data engineering experience
• You do not have hands-on Python for ETL/ELT
• You cannot work from the specified location (Hybrid role)
• You are on a notice period longer than 30 days
• Your background is unrelated (e.g., BI only, support, testing, non-cloud roles)

✅ Apply ONLY if you meet ALL criteria above. Random or irrelevant applications will not be considered

Job Title:

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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.

experienced Senior Data Engineer

The ideal candidate will architect end-to-end data pipelines, automate workflows, ensure data quality, and support advanced analytics and AI workloads across the organization.

AWS data services

Responsibilities

• Architect and implement scalable, fault-tolerant data pipelines using

  AWS Glue, Lambda, EMR, Step Functions, and Redshift

• Build and optimize

  data lakes & data warehouses

  on

  S3, Redshift, Athena

• Develop

  Python-based ETL/ELT frameworks

  and reusable transformation modules
• Integrate data from

  RDBMS, APIs, Kafka/Kinesis, SaaS systems

  into unified datasets
• Lead

  data modeling, schema design, partitioning

  , and performance optimization
• Ensure

  data quality, lineage, and observability

  using AWS Data Catalog, Glue Data Quality, or equivalent tools
• Define and enforce

  data governance, security, and compliance

  (IAM, encryption, access control)
• Collaborate with

  Data Science, Analytics, Product, and DevOps

  teams to support ML and BI workloads
• Implement

  CI/CD pipelines

  for data workflows using AWS CodePipeline, GitHub Actions, or Cloud Build
• Provide

  technical leadership

  , code reviews, and mentoring for junior engineers
• Monitor and optimize data infrastructure, troubleshoot failures, and lead capacity planning

Mandatory Skills

hands-on Data Engineering

Python

AWS Data Services

• AWS Glue, Lambda, EMR, Step Functions

• DynamoDB, Redshift, Athena, S3

• Kinesis, IAM, CloudWatch

✔ Strong SQL, data modeling, performance tuning

data lakes, data warehouses, streaming pipelines

ETL/ELT development

Git

containerization