Job TitlePrincipal, Data & AI Platform Engineer
About the RoleDesign, build, and operate a secure, on-premise analytics and AI platform that unifies transactional data from PostgreSQL, DynamoDB, and other source databases into Snowflake, and applies machine learning, LLMs, and advanced analytics to generate business-critical reports, insights, and operational efficiencies.
This role owns end-to-end technical delivery-from data ingestion and modeling to AI-driven analytics-while ensuring strict data security, governance, and compliance suitable for highly regulated FinTech environments. Public AI services are
not permitted; all AI/ML workloads must run on-prem or in private infrastructure.
What You'll DoData Platform & Snowflake Engineering
- Design and implement secure data pipelines to migrate and unify data from PostgreSQL, DynamoDB, and other source databases into Snowflake.
- Build and optimize ELT/ETL workflows, data models, and schemas in Snowflake for analytics and AI use cases.
- Own Snowflake performance tuning, cost optimization, clustering, and secure data sharing patterns.
- Ensure high data quality, lineage, and reconciliation between source systems and Snowflake.
Analytics & Reporting
- Build analytics datasets and semantic layers to support enterprise reporting, dashboards, and ad-hoc analysis.
- Enable self-service analytics for business and operations teams using governed datasets.
- Collaborate with product and business stakeholders to define KPIs, metrics, and reporting logic.
Machine Learning & LLM Enablement (On-Prem)
- Design and deploy on-prem ML and LLM solutions for reporting automation, anomaly detection, forecasting, and operational insights.
- Implement private / self-hosted LLM architectures (e.g., containerized or VM-based) with secure inference pipelines.
- Develop ML pipelines for feature engineering, training, validation, and inference using enterprise-approved toolchains.
- Integrate AI outputs into applications, workflows, and reporting solutions.
Operational Efficiency via AI
- Implement AI-driven automations for operational efficiencies such as:
- Automated report generation and narrative insights
- Data anomaly detection and monitoring
- Intelligent alerting and triage
- Workflow optimization and decision support
- Measure and continuously improve AI model accuracy, performance, and business impact.
Application & API Integration
- Expose secure APIs and services for data access, analytics, and AI inference.
- Integrate analytics and AI capabilities with existing Java / Spring Boot-based services and applications.
- Follow secure API practices, including authentication, authorization, and token-based access.
Security, Compliance & Governance
- Enforce data security, encryption, access controls, and governance across PostgreSQL, Snowflake, and AI platforms.
- Ensure sensitive FinTech data never leaves approved infrastructure or flows into public AI models.
- Work closely with security teams to support audits, compliance, and risk remediation.
- Apply secure coding practices and address findings from SCA and security scanning tools.
What you will need Data & Analytics
- Strong SQL expertise with PostgreSQL and Snowflake, Data modeling, performance tuning, and optimization
- ETL/ELT frameworks and data orchestration tools
AI / ML
- Hands-on experience with machine learning pipelines and analytics-driven ML use cases
- Experience working with LLMs in private or on-prem environments
- Understanding of prompt engineering, embeddings, vector search, and inference optimization
- Python for ML, data processing, and analytics
Application Development
- Experience integrating analytics and AI into enterprise applications
- Knowledge of microservices and API-driven architectures
Cloud & Platforms
- Experience with Snowflake in enterprise environments
- Hands-on exposure to cloud-native or private cloud platforms (AWS, on-prem, or hybrid)
- Containerization (Docker, Kubernetes) for AI/ML and analytics workloads
Security & Compliance
- Strong understanding of secure data handling, encryption, and access control
- Experience working in regulated environments (FinTech preferred)
- Familiarity with Secure transactions and audit requirements
What You Will Need to Have (Minimum Qualifications)- 8+ years of experience in software engineering, data platforms, or analytics engineering, owning production-grade systems end to end.
- Strong expertise in SQL, with hands-on experience in Snowflake and PostgreSQL, including data modeling, performance tuning, and optimization.
- Proven experience building and operating secure ETL/ELT data pipelines and analytics platforms at enterprise scale.
- Hands-on experience with machine learning and analytics-driven AI use cases (e.g., anomaly detection, forecasting, reporting automation).
- Experience working with LLMs in private or on-prem environments, including inference pipelines, embeddings, or vector search.
- Proficiency in Python for data processing, analytics, and ML workflows.
- Experience integrating analytics and AI capabilities into enterprise applications via APIs and services.
- Familiarity with microservices and REST APIs, including integration with Java / Spring Boot-based services.
- Experience deploying workloads in on-prem, private cloud, or hybrid environments, including containerized deployments (Docker/Kubernetes).
- Strong understanding of data security, encryption, access controls, and operating in regulated environments (financial services, FinTech, or similar).
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Preferred Qualifications- Experience designing enterprise analytics platforms enabling governed, self-service reporting.
- Hands-on experience implementing AI-driven operational automation (automated insights, alerting, or decision support).
- Familiarity with Snowflake cost management, clustering strategies, or secure data sharing.
- Prior exposure to FinTech, payments, or transaction-heavy data domains.
- Experience collaborating with product, business, and security stakeholders on KPI definition and compliance-aligned analytics.
- Experience working in Agile development environments.
Salary Range$110,000.00 - $186,000.00
These pay ranges apply to employees in New Jersey and New York. Pay ranges for employees in other states may differ.
It is unlawful to discriminate against a prospective employee due to the individual's status as a veteran.
For incentive eligible associates, the successful candidate is eligible for an annual incentive opportunity which may be delivered as a mix of cash bonus and equity awards in the Company's sole discretion.
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).
