Data Engineering Delivery, AI Platform Leader
BentoBox
Software Engineering, Data Science
India · Bengaluru, Karnataka, India · Karnataka, India
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 Engineering Delivery, AI Platform LeaderWhat does a successful Data Engineering — AI Platform Lead do?
As the Data Engineering — AI Platform Lead, you will define and build the data and artificial intelligence (AI) platform that supports modern fintech products, operational decisioning, and regulatory reporting. You will work across engineering, product, risk, operations, and governance teams to deliver real-time data products, scalable platform foundations, and reliable machine learning infrastructure. Your work will improve data quality, platform adoption, and delivery speed across transaction and analytical workloads.
What you’ll do:
- Build and lead a senior data engineering organization across streaming, data platform, machine learning (ML) platform, observability, and governance domains
- Define and deliver target architecture for Kafka, Flink, Spark, lakehouse storage, Delta Lake or Apache Iceberg tables, orchestration, data contracts, semantic layers, feature stores, and lineage
- Transform core banking, payments, merchant, customer, risk, dispute, and operational data into governed data products with clear ownership, service level agreements (SLAs), measurable quality controls, and defined business consumers
- Drive migration from legacy batch and report-centric data flows to event-driven data infrastructure that supports AI, fraud, servicing, reconciliation, and regulatory reporting use cases
- Establish operating mechanisms for roadmap reviews, incident management, data quality scorecards, cost management, platform adoption metrics, and executive reporting
- Manage and develop high-seniority engineering talent through hiring, coaching, performance management, and technical leadership across architecture and design reviews
- Define governance controls for personally identifiable information (PII), Payment Card Industry (PCI) data handling, General Data Protection Regulation (GDPR), data retention, data residency, consent, audit trails, encryption, tokenization, and regulatory evidence requirements
- Responsibilities listed are not intended to be all-inclusive and may be modified as necessary.
What you will need to have:
- 13+ years of experience in data engineering, data platform engineering, or distributed data systems within technology, fintech, banking, payments, commerce, or similar regulated environments
- 8+ years of experience defining architecture and delivering large-scale data platforms for real-time transaction processing, governed data products, analytics, or AI and ML use cases
- 5+ years of experience managing and developing teams
- 8+ years of experience using Kafka, Flink, Spark, Databricks, Snowflake, Delta Lake, Apache Iceberg, dbt, Apache Airflow, MLflow, observability tooling, and data governance platforms or similar technologies
- 6+ years of experience designing data platforms for transaction ledgers, settlement files, authorization events, payment scheme data, account master data, customer profiles, merchant hierarchies, and compliance reporting
- 5+ years of experience implementing controls for data privacy, encryption, tokenization, lineage, auditability, retention, and data quality in regulated environments
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field, or equivalent combination of education, related experience and/or military experience
- Experience building feature stores, semantic layers, and reusable data products consumed by AI, operations, risk, and regulatory reporting teams
- Experience modernizing legacy batch data estates into event-driven data architectures
- Experience supporting executive scorecards for platform reliability, lineage, quality, and cost management
What would be great to have:
- Master's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field, or equivalent combination of education, related experience and/or military experience
Travel
This role requires occasional travel to other locations in the country
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.