About the role

Build scalable data foundations and automated pipelines to enable trusted reporting and decision support for business transformation initiatives. Partner with cross-functional teams to map source systems, resolve data gaps, and maintain governed analytics layers.

What they look for

Sql Python Etl/ELT Data Modelling Business Intelligence Data Pipeline Development Cloud Platforms Data Governance Power BI Tableau Alteryx Data Mapping KPI Scorecards Data Quality Analytics Enablement Source Mapping

Requirements

Requires 2-4 years of experience in data engineering or BI with strong proficiency in SQL, Python, and ETL/ELT processes. Candidates should have experience with cloud platforms and the ability to translate business requirements into scalable data structures.

Full description

Calling all innovators – find your future at Fiserv.

We’re Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants, and consumers to one another millions of times a day – quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we’re involved. If you want to make an impact on a global scale, come make a difference at Fiserv.

Job Title

Data Engineer - Business Transformation (SQL, Python, ETL/ELT, data modelling, and BI) || Noida

Data Engineer - Business Transformation

What does a great Data Engineer - Business Transformation do?

As a Data Engineer - Business Transformation, you will build scalable data foundations that enable trusted reporting, analytics, and decision support across key transformation initiatives.

Work on Fiserv’s biggest priorities alongside its senior-most leaders. Own high-impact initiatives end to end, learn from exceptional peers, and help shape the future of the business.

This role sits at the intersection of data engineering, governance, business intelligence, and analytics enablement. You will partner with business, technology, finance, operations, and analytics teams to map source systems, resolve data gaps, build automated pipelines, and create reliable data assets for recurring decision-making.

The ideal candidate brings strong SQL, Python, ETL/ELT, data modelling, and BI capabilities, with a practical understanding of data quality, governance, and stakeholder needs.

What You'll Do

Data Foundations & Source Mapping

Identify source systems, data owners, key fields, dependencies, and data gaps required for decision support.
Partner with business and technology teams to document data flows, lineage, metric definitions, and reporting requirements.
Establish common data models, reusable datasets, and governed analytics layers to improve consistency across initiatives.

Data Pipelines & Automation

Build automated data flows from source systems to analytics, reporting, and dashboard layers.
Develop, test, and maintain ETL/ELT processes using SQL, Python, and modern data platform tools.
Monitor pipeline reliability, data quality, refresh timelines, and issue resolution to ensure trusted reporting outputs.

Dashboards, Metrics & Governance

Build and maintain dashboards, recurring views, KPI scorecards, and key data assets for transformation programs.
Standardize analytical logic, metric definitions, data dictionaries, and documentation across priority initiatives.
Support governance practices related to access, data quality, metadata, and usage consistency.

What you will need to have:

2-4 years of experience in data engineering, data platforms, business intelligence, or related data functions.
Strong SQL, Python, ETL/ELT, data modelling, and data pipeline development skills.
Experience working with cloud platforms, BI tools, data governance practices, and automated reporting frameworks.
Ability to understand business requirements and translate them into scalable data structures and reusable assets.
Strong problem-solving skills with attention to detail, data quality, and documentation.

Experience That Would Be Great to Have

Experience in merchant data infrastructure, billing, payments, fintech, or financial services environments.
Exposure to AI-enabled use cases, semantic layers, data catalogues, and analytics modernization initiatives.
Experience with BI and analytics tools such as Power BI, Tableau, SQL, Alteryx, Python, R, or similar technologies.
Prior experience supporting executive dashboards, KPI standardization, and enterprise reporting programs.

Thank you for considering employment with Fiserv. Please:

Apply using your legal name
Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).

Our commitment to Diversity and Inclusion:

Fiserv is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, protected veteran status, or any other category protected by law.

Note to agencies:

Fiserv does not accept resume submissions from agencies outside of existing agreements. Please do not send resumes to Fiserv associates. Fiserv is not responsible for any fees associated with unsolicited resume submissions.

Warning about fake job posts:

Please be aware of fraudulent job postings that are not affiliated with Fiserv. Fraudulent job postings may be used by cyber criminals to target your personally identifiable information and/or to steal money or financial information. Any communications from a Fiserv representative will come from a legitimate Fiserv email address.