Lead Data Engineer

Tech Mahindra · IT Consulting & Digital Transformation · IT Outsourcing & Dedicated Teams · Python · SQL · ETL/ELT · AWS Glue · 1 day ago
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Location
In office (Juno Beach)
Seniority
Staff
Visa
H-1B filings in 12 months: 786 · for this role: 20 · green card filings: 5

Confirmed on the employer's own hiring board on Nov 11, 2026. First seen by Alion on Nov 9, 2026. Tech Mahindra scores A on the Alion truth index.

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Tech Mahindra

Tech Mahindra is a prominent Indian multinational information technology services and consulting enterprise specializing in digital transformation, cloud modernization, business process re-engineering, and network services. Headquartered in Pune, Maharashtra, India (with its registered office in Mumbai), the company is a flagship entity of the diversified Mahindra Group conglomerate. Established in 1986 (initially as Mahindra British Telecom), it operates across dozens of countries with a global delivery footprint serving enterprise clients in telecommunications, banking and financial services, healthcare, automotive, and retail. The organization is particularly recognized for its deep engineering heritage in telecommunications and 5G network integration, offering end-to-end solutions spanning artificial intelligence, enterprise application management, customer experience (CX), and next-generation connectivity infrastructure.
techmahindra.com · HQ: Pune, India · Systems Integrators · Business Process Outsourcing (BPO) · IT Consulting & Digital Transformation · IT Outsourcing & Dedicated Teams · Est. 1986
Tech stack of Tech Mahindra
Backed by Seafund

Job Description

  • Skill Set :

    AWS Data Engineer

  • Total Experience :

    8.00 to 10.00 Years

  • No of Openings :

    1

  • Job Post Date :

    15/10/2026

  • Job Expiry Date :

    30/11/2026

  • Domain :

    IT

  • Location :

    JUNO BEACH [United States]

  • Job Reference No :

    4113074

Job Summary

Hands on data engineering experience with proven track record of building production data pipelines

Expert level proficiency in Python for data processing, ETL development, and automation (PySpark)

Deep experience with AWS Glue including job development, crawlers, triggers, and workflow orchestration

Strong expertise in DynamoDB data modeling, capacity planning, streams, and performance optimization

Solid understanding of AWS ecosystem: S3, Lambda, Step Functions, CloudWatch, IAM, KMS, Kinesis

Proficiency with Postman for API development, testing, and collaboration

Strong SQL skills and understanding of data warehousing principles

Experience with version control (Git), CI/CD tools, and infrastructure as code (CloudFormation/Terraform)

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