Data Service Layer AI Engineer

About the Role 

Position Title: Data Service Layer AI Engineer

Corporate Title: Senior Analyst

Reporting to: Vice President

Job Profile 

Position details:

Cloud Data Engineer and Data Visualization Specialist with a strong technology background and hands-on experience working in an enterprise environment, designing and implementing data warehouses, data lakes, and data marts for large financial institutions. The ideal candidate will have BI & Analytics experience along with expertise in Data Engineering, Data Pipelines, and modern AI-assisted development practices. In this role, you will work with technology and business leads to build or enhance critical enterprise applications both on-prem and in the cloud (AWS), leveraging modern data platforms such as Snowflake and Starburst for semantic layer and data virtualization solutions. Candidates should also have experience applying AI-enabled productivity tools such as GitHub Copilot and exposure to Agentic AI frameworks, Prompt Engineering, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) concepts to drive automation and innovation. Successful candidates will possess in-depth knowledge of current and emerging technologies, demonstrate a passion for designing and building elegant solutions, and continuously explore opportunities to improve engineering efficiency through responsible adoption of AI technologies.

Requirements

Roles and Responsibilities:

· Manage data analysis and data integration of disparate systems using data virtualization platforms

· Develop and implement data mesh and data fabric architectures to enable decentralized data management and access.

· Perform federated querying to access and analyze data across different data sources.

· Develop user personas and business personas in alignment with data requirements and deliver solutions that meet business needs.

· Work with business users to translate functional specifications into technical designs for implementation and deployment

· Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes, SaaS solutions such as snowflake or cloud-based data warehouses.

· Leverage GitHub Copilot and AI-assisted development tools to improve productivity, code quality, documentation, and testing efficiency.

· Design and implement AI-enabled automation solutions, including Agentic AI frameworks, to enhance data engineering, reporting, and operational processes.

· Work with cross functional team members to develop prototype, produce design artifacts, develop components, perform and support SIT and UAT testing, triaging and bug fixing.

· Optimize and fine-tune data pipeline jobs for performance and scalability.

· Implement data quality and data validation processes to ensure data accuracy and integrity.

· Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs

· Convert physical data integration models and other design specifications to source codes

· Ensure high quality and optimum performance of data integration systems to meet business solutions

Job Requirements:

Bachelors’ Degree (or foreign equivalent degree) in Information Technology, Information Systems, Computer Science, Software Engineering, or related field. Experience in the financial services or banking industry is preferred.

· 5+ years of experience with data virtualization, data mesh, data fabric, and federated querying platforms such as Denodo, Starburst or OSS platforms is highly desirable.

· 5+ Years of experience working as a Report Visualization Engineer with Power BI, Tableau, or any similar Reporting Platforms with End-to-End delivery.

· 3+ Year of experience with implementation of Data Modelling, Data Governance and RLS.

· 3+ Years of experience with Enterprise Deployment Strategies and migration of legacy platform reports to modern reporting platforms.

· 2+ years of hands-on experience using GitHub Copilot or similar AI-assisted engineering tools to accelerate software development, analytics, and automation workflows.

· 2+ years of experience building or working with Agentic AI solutions, Prompt Engineering, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI governance principles.

· Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes or modern data platforms like Snowflake.

· Assist Data Management Engineering Team (either for Data Pipelines Engineering or Data Service & Data Access Engineering) for ETL or BI Design and other framework related items.

· Solid understanding of data modeling, database design, and ETL principles.

· Experience working with data lakes, data warehouses, and distributed computing systems.

· Familiarity with data governance, data security, and compliance practices in cloud environments.

· Strong problem-solving skills and the ability to optimize and fine-tune data pipelines and Spark jobs for performance.

· Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

· Tableau/Power BI / Snowflake / Starburst certifications on Data related specialties are a plus.

· Power Platform experience (Power Apps, Power Automate) will be a plus.

Business Acumen – 15%: Knowledge of Banking & Financial Services Products (such as Loans, Deposits, Forex, etc.). Knowledge of Operational/MIS Reports, Risk, and Regulatory Reporting for a US Bank is a plus.

Data Skills – 25%: Must have proficiency in Data Warehousing concepts, Data Lake & Data Mesh concepts, Data Modeling, Databases, Data Governance, Data Security/Protection, and Data Access.

Tech Skills – 50%: See above

Human Skills – 10%: Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

Equal Opportunity Employer

We are committed to providing equal employment opportunities to all applicants and employees and does not discriminate on the basis of race, colour, national origin, physical appearance, religion, gender expression, gender identity, sex, age, ancestry, marital status, disability, medical condition, sexual orientation, genetic information, or any other protected status of an individual or that individual's associates or relatives, or any other classification protected by the applicable law

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