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Salary
≈ $17k – $36k per year (Estimated)
Location
Hybrid (Pune, India)
Seniority
Staff
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 20, 2026. Genpact scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Genpact is a professional services company that began in 1997 as a business process unit inside GE Capital in India, and was spun out as an independent firm in 2005. It runs finance and accounting, supply chain, procurement, risk and customer operations on behalf of large enterprises, combining offshore delivery with process reengineering and increasingly with automation rather than pure labour arbitrage. Headquartered in New York and listed on the New York Stock Exchange, the company employs well over a hundred thousand people, mostly in India, and has repositioned its offering around agentic AI embedded into the processes it already operates.
Lead Data Engineer

Ready to turn bold ideas into real-world impact?

At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory, our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI, our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment.

Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises.

Get to know us at genpact.com and on LinkedIn, YouTube, X, and Facebook.

Job Description

We are seeking a skilled Data Quality Engineer to design, build, and operationalize a Data Quality Factory - a standardized, scalable framework for profiling, validating, monitoring, and remediating data quality issues across enterprise data platforms. The ideal candidate will bring hands-on expertise across Azure AI Foundry, Python, SQL, Databricks, and Snowflake, and will play a key role in embedding automated data quality checks, rules, and dashboards into modern data pipelines.

Key Responsibilities

  • Design and implement a reusable Data Quality Factory framework covering profiling, rule-based validation, anomaly detection, and reconciliation across source and target systems.
  • Build and maintain data quality rules, scorecards, and dashboards to track completeness, accuracy, consistency, timeliness, and uniqueness metrics.
  • Develop and deploy data quality pipelines using Databricks (PySpark/Spark SQL) and Snowflake (SQL, Snowpark) for large-scale data validation.
  • Leverage Azure AI Foundry to build and integrate AI/ML-assisted data quality checks (e.g., anomaly detection, intelligent rule suggestions, GenAI-based DQ remediation).
  • Write efficient, production-grade Python and SQL scripts for automated data profiling, cleansing, and exception handling.
  • Integrate data quality checks into CI/CD pipelines and orchestration tools to enable automated, scheduled DQ runs.
  • Collaborate with data engineering, governance, and business teams to define DQ rules, thresholds, and remediation workflows.
  • Perform root cause analysis on data quality issues and drive resolution with upstream data owners.
  • Document data quality standards, metadata, and lineage to support data governance initiatives.
  • Support audit and compliance requirements by maintaining data quality logs, exception reports, and control evidence.

Required Skills

  • Azure AI Foundry - hands-on experience building/deploying AI-assisted solutions or agents.
  • Python - strong programming skills for data validation, automation, and scripting.
  • SQL - advanced query writing, performance tuning, and complex data validation logic.
  • Databricks - experience with Delta Lake, notebooks, and job orchestration.
  • Snowflake - experience with Snowflake SQL, Snowpark, warehouses, and data sharing.
  • Strong understanding of data quality dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness).
  • Familiarity with data governance, data cataloguing, and metadata management concepts.
  • Experience integrating DQ frameworks with CI/CD and orchestration tools (e.g., Airflow, ADF, DevOps pipelines).

Good to Have

  • Experience with data quality tools (e.g., Great Expectations, Collibra, Informatica DQ, Ataccama).
  • Exposure to Azure Data Factory, Azure Synapse, or other Azure data services.
  • Knowledge of data lineage and cataloguing tools.
  • Experience working in regulated industries (finance, healthcare, insurance) with strict data quality/compliance needs.

Qualifications

  • Bachelor's/master’s degree in computer science, Information Systems, Engineering, or related field.
  • [4-6] of experience in data engineering / data quality roles.
  • Relevant certifications (Databricks, Snowflake, Azure) are a plus.

Soft Skills

  • Strong analytical and problem-solving mindset.
  • Ability to work with cross-functional teams (engineering, governance, business).
  • Excellent communication skills to document and present data quality findings.
  • Self-driven, detail-oriented, and comfortable working in a fast-paced environment.

Qualifications

Bachelors - Business Analytics, Bachelors - Computer Science, Bachelors - Statistics, Masters - Data Science

Certifications

Certified Data Management Professional - RiversandRiversand, Databricks Certified Associate Developer for Apache Spark 3.0 - Databricks AcademyDatabricks Academy, Databricks Certified Associate Developer for Apache Spark - Databricks AcademyDatabricks Academy, Microsoft Certified: Azure Data Engineer Associate - MicrosoftMicrosoft, Oracle Database 12c Certified Implementation Specialist - OracleOracle

Required Skills

Agile Methodology, Cloud Computing, Collaboration Tools, Commercial Sales, Consumer Packaged Goods (CPG), Databricks Platform, Data Engineering, Data Literacy

Language

English

Language Proficiency -

Proficient - C2

Additional Job Location -

Job Type

Regular

Master Skill List -

Data Engineering

Remote Type -

Hybrid

Work Shift -

Flex Time (India)

Why join Genpact?

  • Lead AI-powered transformation - Drive innovation and solve real-world business challenges that matter
  • Make an impact - Help global enterprises solve business challenges that matter
  • Accelerate your career - Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead
  • Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day
  • Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.
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