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Engineer Lead, Data

Pune, Mahārāshtra, India

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Employment
Full-time — employment source
Position Type : Full time Type Of Hire : Experienced (relevant combo of work and education)The future of money is being built right now. At FIS, we help the world’s businesses, banks and communities move, manage and grow money with confidence. Join a team that values fresh thinking, works together to solve complex challenges, and creates technology that powers everyday life.
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What you’ll work on

Full posting

As a Data Engineer, AI Governance, you will design, build, and maintain the data foundations that support responsible, trusted, and scalable AI across FIS.

Design, develop, and maintain scalable backend data pipelines, integrations, and data platforms that support AI governance and analytics initiatives.

  • Build and maintain scalable backend data pipelines and integrations for AI governance and analytics

  • Consolidate and transform enterprise data into trusted, governed datasets

  • Establish and maintain end-to-end data lineage

  • Implement data quality controls, monitoring, and observability

  • Help define, automate, and monitor data access controls

From the employer’s posting
As a Data Engineer, AI Governance, you will design, build, and maintain the data foundations that support responsible, trusted, and scalable AI across FIS. This role combines deep backend engineering expertise with a passion for data quality, governance, and transparency. You will serve as a data wrangler and problem solver, ensuring data is discoverable, traceable, reliable, and fit for purpose while providing visibility into data lineage, ownership, and usage throughout the enterprise.
Design, develop, and maintain scalable backend data pipelines, integrations, and data platforms that support AI governance and analytics initiatives.
Consolidate and transform data from multiple enterprise sources into trusted, governed datasets for AI and business consumption.
Establish and maintain end-to-end data lineage, enabling visibility into where data originates, how it is transformed, and how it is consumed.
Implement data quality controls, monitoring frameworks, and observability practices to proactively identify and resolve data issues.
Support data access governance by helping define, automate, and monitor data access controls and permissions.

What you’ll bring

All qualifications

Core experience

  • Experience as a Data Engineer, Data Platform Engineer, Data Integration Engineer, or similar role supporting large-scale data environments.
  • Strong experience building and supporting backend data pipelines using modern data engineering practices.
  • Experience with data integration, transformation, cleansing, and consolidation across multiple data sources.
  • Strong understanding of data governance, data quality, metadata management, and data lifecycle management.
  • Experience establishing and documenting data lineage, data flows, and data dependencies.
  • Proficiency with SQL and data modeling concepts in enterprise data environments.

Preferred experience

  • Experience supporting AI, machine learning, or responsible AI governance programs.
  • Familiarity with data catalog, metadata management, data lineage, or data observability platforms.
  • Experience implementing enterprise data quality and monitoring frameworks.
  • Experience within financial services, fintech, payments, banking, or highly regulated industries.
Qualification wording
Experience as a Data Engineer, Data Platform Engineer, Data Integration Engineer, or similar role supporting large-scale data environments.
Strong experience building and supporting backend data pipelines using modern data engineering practices.
Experience with data integration, transformation, cleansing, and consolidation across multiple data sources.
Strong understanding of data governance, data quality, metadata management, and data lifecycle management.
Experience establishing and documenting data lineage, data flows, and data dependencies.
Proficiency with SQL and data modeling concepts in enterprise data environments.
Experience supporting AI, machine learning, or responsible AI governance programs.
Familiarity with data catalog, metadata management, data lineage, or data observability platforms.
Experience implementing enterprise data quality and monitoring frameworks.
Experience within financial services, fintech, payments, banking, or highly regulated industries.

Tools in this posting

  • SQL
Source — Tool mentions in context
- Experience establishing and documenting data lineage, data flows, and data dependencies. - Proficiency with SQL and data modeling concepts in enterprise data environments. - Experience with cloud-based data platforms, data warehouses, and data lake architectures.

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 28, 2026 · 2 days ago
Recorded sightings
5
Last seen by us
Oct 30, 2026

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Job description

View original posting ↗

Position Type :

Full time

Type Of Hire :

Experienced (relevant combo of work and education)

The future of money is being built right now. At FIS, we help the world’s businesses, banks and communities move, manage and grow money with confidence. Join a team that values fresh thinking, works together to solve complex challenges, and creates technology that powers everyday life.

 

About the role

As a Data Engineer, AI Governance, you will design, build, and maintain the data foundations that support responsible, trusted, and scalable AI across FIS. This role combines deep backend engineering expertise with a passion for data quality, governance, and transparency. You will serve as a data wrangler and problem solver, ensuring data is discoverable, traceable, reliable, and fit for purpose while providing visibility into data lineage, ownership, and usage throughout the enterprise.

Your key responsibilities

  • Design, develop, and maintain scalable backend data pipelines, integrations, and data platforms that support AI governance and analytics initiatives.
  • Consolidate and transform data from multiple enterprise sources into trusted, governed datasets for AI and business consumption.
  • Establish and maintain end-to-end data lineage, enabling visibility into where data originates, how it is transformed, and how it is consumed.
  • Partner with business, technology, and governance teams to define data ownership, stewardship, and accountability models.
  • Implement data quality controls, monitoring frameworks, and observability practices to proactively identify and resolve data issues.
  • Develop metadata management processes that improve data discoverability, traceability, and governance compliance.
  • Support data access governance by helping define, automate, and monitor data access controls and permissions.
  • Build and maintain data validation, reconciliation, and audit capabilities that improve trust in enterprise data assets.
  • Collaborate with AI, machine learning, and analytics teams to ensure governed data is available for model development and operational use cases.
  • Recommend and implement automation opportunities that improve data reliability, efficiency, and operational excellence.

What you bring

Required qualifications

  • Experience as a Data Engineer, Data Platform Engineer, Data Integration Engineer, or similar role supporting large-scale data environments.
  • Strong experience building and supporting backend data pipelines using modern data engineering practices.
  • Experience with data integration, transformation, cleansing, and consolidation across multiple data sources.
  • Strong understanding of data governance, data quality, metadata management, and data lifecycle management.
  • Experience establishing and documenting data lineage, data flows, and data dependencies.
  • Proficiency with SQL and data modeling concepts in enterprise data environments.
  • Experience with cloud-based data platforms, data warehouses, and data lake architectures.
  • Knowledge of data security, access management, and governance principles.
  • Strong analytical, troubleshooting, and problem-solving skills with exceptional attention to detail.
  • Passion for creating high-quality, trusted, and well-governed data products.

Preferred qualifications

  • Experience supporting AI, machine learning, or responsible AI governance programs.
  • Familiarity with data catalog, metadata management, data lineage, or data observability platforms.
  • Experience implementing enterprise data quality and monitoring frameworks.
  • Experience within financial services, fintech, payments, banking, or highly regulated industries.

The impact you’ll make

As a Data Engineer, AI Governance, you will help establish confidence in the data that powers AI and business decision-making across FIS. Your work will enable clear visibility into data origins, transformations, ownership, and consumption while ensuring high standards of quality, accessibility, and governance. By building trusted data foundations, you will play a critical role in advancing responsible AI adoption and delivering scalable solutions that create long-term value for the organization.

 

What we offer you

Bring your ideas. Build your future. At FIS, you'll find the support, resources and opportunities to develop your career while helping shape the future of financial technology.

We offer:

  • Internal career growth opportunities
  • Opportunities to innovate in fintech
  • Inclusive and diverse team atmosphere
  • Professional and personal development
  • Resources to contribute to your community

 

Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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Location & working pattern

Pune, Mahārāshtra, India

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