Principal, Data & AI Platform Engineer

Design, 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 Do

Data 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.

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.

$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.

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.