Data Engineering Practice Head

8 - 10 years

0 Lacs

Posted:5 days ago| Platform: Foundit logo

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Job Type

Full Time

Job Description

Test

Yantra

Software Solutions is a global technology powerhouse with 5000+ employees delivering excellence across software testing, digital product engineering, and IT services. With a strong footprint across India, the USA, the UK, the Netherlands, Australia and Canada, Test Yantra partners with enterprises worldwide to accelerate innovation, ensure quality, and build future-ready digital ecosystems.As part of the diversified Test Yantra Global group, the company extends its impact through specialised verticals:

TechnoElevate

offering end-to-end IT solutions, custom development, cloud, and digital transformation services.

FireFlink

a next-gen codeless automation platform enabling rapid, intelligent, and scalable test automation.

QSpiders

&

JSpiders

the world's largest software testing and development training organisation, shaping thousands of tech careers every year.Driven by a culture of innovation, customer-centricity, and deep technical expertise, Test Yantra continues to empower businesses across industries with reliable, scalable, and cutting-edge technology solutions

Role Overview

We are seeking a highly experienced

Data Engineering Practice Head

to lead, scale, and strengthen our Data Engineering capability. This role requires a seasoned leader with deep hands-on expertise in modern data engineering technologies including

Python, SQL, Data Warehousing, Data Engineering, Spark/PySpark, and Databricks

. The ideal candidate will drive end-to-end delivery of complex data programmes; define standards, best practices, and governance; and build a world-class data engineering team capable of supporting global clients.

Key Responsibilities

  • Lead the Data Engineering Practice by defining strategy, capability roadmap, best practices, and delivery frameworks to drive innovation and excellence across projects.
  • Build, lead, and scale a high-performing global Data Engineering team, including coaching, performance management, and career development.
  • Establish and run structured training, certification pathways, and competency uplift programmes to continuously strengthen technical capabilities across the practice.
  • Oversee end-to-end project delivery including requirement analysis, solution design, development, testing, deployment, and post-production support for complex Data Engineering and cloud modernisation initiatives.
  • Guide customers as a trusted advisor, managing expectations, leading solution discussions, and supporting roadmap creation, POCs, and long-term adoption of data platforms.
  • Drive optimisation and continuous improvement in data pipelines, governance, security, observability, and operational efficiency.
  • Support pre-sales activities including solutioning, scoping, estimations, proposal creation, and stakeholder presentations.

Required Skills & Experience

  • 8+ years of IT experience, with significant hands-on exposure to end-to-end data engineering.
  • Strong programming skills in Python, including EDA and data manipulation.
  • Expertise in SQL, database design, optimisation, and data modelling.
  • Strong foundational knowledge in Data Warehousing, ETL/ELT pipelines, and multi-dimensional modelling.
  • Proven experience with Data Engineering services(Azure/AWS/GCP) and modern cloud data architectures.
  • Proficiency in Spark and PySpark for distributed data processing.
  • Strong hands-on experience with Databricks in enterprise environments.
  • Excellent leadership skills with proven experience managing large data engineering teams.
  • Strong customer-facing, communication, and stakeholder management capabilities.
  • Ability to drive practice-level initiatives including governance, delivery excellence, and capability building.

Preferred Qualifications

  • Experience in pre-sales solutioning, data platform migration, or modern data stack implementations.
  • Experience working with global customers across BFSI, Retail, Telecom, Manufacturing, or Healthcare.
  • Experience with DevOps for data, orchestration pipelines, CI/CD, or data observability tools.

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