Sr Data Engineer- Data Platform & AI Enablement

Citizens; Johnston (RI); On-site; USD 120,000 - 180,000; Full time

Job summary

Citizens is seeking a Senior Data Engineer to design and maintain scalable data pipelines, enabling AI-ready data foundations for analytics, ML, and GenAI workloads. You will collaborate with data scientists, architects, and product teams to build secure, governed data platforms supporting large-scale financial data operations.

The role emphasizes production-grade code, data modeling, and implementing metadata, lineage, governance, and compliance across enterprise data frameworks.

Qualifications

• 6-8+ years of experience in data engineering and distributed data processing technologies.
• Hands-on experience with streaming technologies such as Apache Spark, Beam, or Flink.
• Experience with message brokers such as Apache Kafka.
• Experience working with microservices and batch processing systems.
• Strong programming skills in Java and/or Scala; Python experience preferred.
• Strong SQL development and performance optimization skills.
• Relational databases (Redshift, PostgreSQL, Snowflake) and NoSQL (MongoDB).
• CI/CD pipelines and version control systems such as Bitbucket and Git.
• ETL tools such as Talend or DataStage are a plus.
• Java Spring Boot; familiarity with React, TypeScript, or Angular is a plus.
• Cloud data processing with AWS and/or Azure experience preferred.
• Experience with AI/GenAI concepts and LLM-based applications.
• Governance, security, and compliance in regulated environments.
• Workflow orchestration and MLOps/LLMOps exposure.

Responsibilities

• Design, build, and maintain data pipelines to acquire, transform, and store large datasets.
• Develop pipelines to collect and compute metrics from financial data sources while ensuring quality.
• Contribute to architecture and data framework patterns with engineers and architects.
• Collaborate with cross-functional teams to deliver data solutions meeting business needs.
• Develop production-ready, high-quality code.
• Apply database design principles and data modeling for scalable solutions.
• Develop and optimize data models for analytics, ML, and AI use cases.
• Support enterprise data frameworks and reusable capabilities across the organization.
• Identify opportunities to improve existing frameworks and build reusable components.
• Troubleshoot data-related issues; perform unit testing and support UAT and deployment.
• Follow change management and compliance standards.
• Build pipelines and platform capabilities that support AI, GenAI, and agentic AI use cases.
• Develop governed, high-quality datasets for ML/LLM and automation.
• Create pipelines for structured, semi-structured, and unstructured data to support GenAI capabilities like semantic search and retrieval-augmented generation.
• Partner with data scientists and product teams to integrate AI/GenAI into platforms and workflows.

Skills

Spark/Beam/Flink

Apache Kafka

Java/Scala

Python

SQL

Redshift/PostgreSQL/Snowflake

MongoDB

CI/CD (Bitbucket/Git)

Talend/DataStage

Spring Boot

React/TypeScript/Angular

AWS/Azure

LLM/GenAI concepts

Education

Bachelor’s degree in Computer Science, Engineering, or a related technology field

Tools

Talend

DataStage

Bitbucket

Git

Job description

Senior Data Engineer – Enterprise Data Enablement

The Enterprise Data Enablement team is seeking a Senior Data Engineer who can design, develop, and maintain secure, scalable, and efficient data pipelines and platforms. This role will focus on building and deploying data solutions across financial consumer business domains by leveraging existing and new data framework capabilities to acquire, transform, stream, and integrate data. The candidate will also contribute to innovative data engineering solutions, including AI/GenAI/Agentic AI-ready data capabilities, while collaborating with and supporting a team of data engineers in building scalable, secure, and intelligent data platforms.

Primary Responsibilities

• Design, build, and maintain reliable, efficient, and scalable data pipelines to acquire, transform, and store large datasets.
• Develop robust data pipelines to collect, process, and compute metrics from various financial data sources while adhering to quality and development standards.
• Contribute to application architecture and technical solutions, and help implement data framework patterns alongside senior engineers and architects.
• Collaborate with cross-functional teams to deliver optimal data solutions that meet business and platform needs.
• Develop and deploy high-quality, production-ready code.
• Apply strong database design principles and data modeling techniques to translate business requirements into scalable data solutions.
• Develop and optimize data models to support analytics, reporting, machine learning, and AI-driven use cases.
• Support the implementation and enhancement of enterprise data frameworks and contribute to scalable solutions.
• Identify opportunities to improve existing frameworks and help build reusable capabilities across the organization.
• Troubleshoot and resolve data-related issues in a timely manner.
• Execute unit testing for data pipelines, validate results, and ensure data quality and accuracy; partner with business users for User Acceptance Testing and support deployment activities.
• Follow change management practices and ensure adherence to compliance and regulatory standards.
• Design and build data pipelines and platform capabilities that support AI, Generative AI, and Agentic AI use cases, including model training, inference, retrieval, and orchestration workflows.
• Enable AI-ready data foundations by developing high-quality, governed, and reusable datasets for machine learning, large language model (LLM), and intelligent automation solutions.
• Develop and optimize pipelines for structured, semi-structured, and unstructured data to support GenAI use cases such as semantic search, document intelligence, and retrieval-augmented generation (RAG).
• Partner with data scientists, ML engineers, architects, and product teams to integrate AI/GenAI capabilities into enterprise data platforms and workflows.
• Implement metadata, lineage, governance, security, and access controls required for responsible AI and enterprise-scale GenAI adoption.
• Ensure observability, reliability, performance, and data quality for data pipelines, including those supporting AI-enabled workflows.

Required Skills / Experience

• 6-8+ years of experience in data engineering and distributed data processing technologies.
• Hands-on experience with streaming technologies such as Apache Spark, Beam, or Flink.
• Experience with message brokers such as Apache Kafka.
• Experience working with microservices and batch processing systems.
• Strong programming skills in Java and/or Scala; Python experience preferred.
• Strong SQL development and performance optimization skills.
• Solid knowledge of relational databases (Redshift, PostgreSQL, Snowflake) and NoSQL databases (MongoDB or similar).
• Experience with CI/CD pipelines and version control systems such as Bitbucket and Git.
• Experience with ETL development tools such as Talend or DataStage is a plus.
• Experience with Java Spring Boot; familiarity with React, TypeScript, or Angular is a plus.
• Understanding of cloud-based data processing, with AWS and/or Azure experience preferred.
• Experience building data pipelines that support analytics, machine learning, and AI workloads.
• Working knowledge of data engineering concepts supporting LLM-based applications, including retrieval pipelines, embeddings workflows, and unstructured data processing.
• Familiarity with AI/GenAI concepts such as RAG, semantic search, document processing, and model inference workflows.
• Understanding of data governance, security, lineage, and compliance requirements, particularly in regulated environments.
• Exposure to workflow orchestration frameworks and automation patterns is a plus.
• Exposure to vector databases, semantic models, or MLOps/LLMOps concepts is a plus.
• Strong analytical and problem-solving skills, with the ability to collaborate effectively within technical teams.

Education, Certifications, And/or Other Professional Credentials

• Bachelor’s degree in Computer Science, Engineering, or a related technology field

Hours and Work Schedule

• Hours per Week: 40
• Work Schedule: Monday through Friday

Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague’s or a dependent’s reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Why Work for Us

At Citizens, you'll find a customer-centric culture built around helping our customers and giving back to our local communities. When you join our team, you are part of a supportive and collaborative workforce, with access to training and tools to accelerate your potential and maximize your career growth

Posting End Date: 09/30/2026