Assistant Vice President Data Service Layer AI Engineer

About the Role

Position Title: Assistant Vice President – Data Service Layer AI Engineer

Corporate Title: Assistant Vice President

Reporting to: Vice President

Location: - Bengaluru

Job Profile

Position details

Experienced Data Services Delivery Leader with a strong blend of technical expertise and business acumen, responsible for leading the strategy, design, implementation, and delivery of enterprise data engineering, data integration, reporting, and analytics solutions across on-premises and cloud platforms. The role drives data aggregation, reconciliation, governance, and modernization initiatives leveraging AWS, Snowflake, Starburst, and related technologies, while partnering with business and technology stakeholders to deliver scalable, high-quality solutions. The ideal candidate will have deep expertise in modern data architectures, BI and analytics platforms, and AI-enabled engineering practices, including GitHub Copilot, Agentic AI, Prompt Engineering, LLMs, and RAG, with a passion for driving innovation, automation, and engineering excellence through the responsible adoption of emerging technologies.

Job Requirements:

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

· Required Skills:

o 8+ years of experience leading design, development, and optimization of dashboards and reports using Power BI, Tableau, and other reporting platforms.

o 5+ years of experience with integration of BI tools with data warehouses/ lakes (e.g. Snowflake), along with strong knowledge of Data Modelling, UX/UI for Dashboards.

o 3+ years of experience with migration of reports from legacy platforms.

o 5+ Years of Strong proficiency in AWS services, including AWS Glue, Redshift, EMR, RDS, Kinesis, S3, Athena, DynamoDB, Step Functions and Lambda.

o 2+ Years of Expertise in dealing with data pipelines associated with modern data platforms such as Snowflake.

o 4+ years of hands-on experience with AI-assisted engineering tools such as GitHub Copilot or similar platforms, with practical understanding of how these tools can improve development, documentation, testing, and automation workflows.

o 2+ years of working experience with Agentic AI concepts, Prompt Engineering, Large Language Models, Retrieval-Augmented Generation, AI governance, and responsible AI adoption in enterprise technology environments.

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

· Desirable Skills:

o Exposure to Data Virtualization tools such as Starburst, Dremio or Denodo is a plus; Familiarity with data mesh, data fabric is highly desirable.

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

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%:

· BI Tools: Power BI (Desktop, Service), Tableau (Desktop, Server, Online, Prep).

o Advanced: DAX (Good to have)

· Data Modelling: Star & Snowflake Schema, Composite Models, RLS, Data Blending

· Cloud Technology: AWS (Redshift, S3, Athena) , Storage – S3 Buckets

· Virtualization Layer: Denodo, Dremio, Starburst

· AWS Cloud technology stack (EMR, Redshift, HiveQL, Glue, RDS, etc.)

· Databases: SQL Server , Oracle

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