Mid/Senior Analytics Engineer

About the role:

The Analytics Engineer is responsible for building and maintaining Bank X's analytics layer, transforming raw and curated data into trusted, reusable, and business-ready data products. The role sits between Data Engineering, Business Analytics, AI Engineering, and business stakeholders, ensuring that data is understandable, governed, performant, and ready for decision-making and AI consumption.

As Bank X evolves into an AI-native digital bank, Analytics Engineers ensure that both human users and AI agents consume consistent definitions, reliable datasets, and reusable business logic across domains such as customer, product, transaction, risk, finance, and operations.

Key Responsibilities:

Analytics Data Products

• Design, build, and maintain curated data marts, semantic models, and business-ready datasets for reporting, analytics, experimentation, and AI use cases.

• Transform complex raw data into clean, documented, reusable analytical assets that business users and AI agents can consume with confidence.

• Improve performance, usability, and discoverability of analytical datasets across the organization.

Semantic Layer & Business Logic

• Define, implement, and maintain standardized business metrics, KPI definitions, dimensions, and calculation logic.

• Ensure consistency of business logic across dashboards, regulatory reporting, self-service analytics, AI applications, and agentic workflows.

• Translate business requirements into scalable analytical models and reusable data structures.

AI-Ready Data Foundation

• Create AI-ready datasets and Customer 360 views to support AI Customer Service, AI Money Coach, personalization, next-best-action, and future AI-native banking capabilities.

• Design data products optimized for retrieval, reasoning, recommendation, and AI-powered decision support.

• Collaborate with AI Engineers to define data requirements, feature-ready structures, metadata, and context required by AI agents.

Data Quality, Governance & Documentation

• Implement validation rules, reconciliation checks, and monitoring controls for critical analytical data products.

• Document ownership, data lineage, business definitions, assumptions, refresh logic, and known limitations.

• Ensure compliance with data governance, security, privacy, and banking regulatory expectations.

Self-Service Analytics Enablement

• Enable business teams to answer questions independently through governed data products and clear semantic models.

• Support dashboard, reporting, and analytical use cases by providing consistent, trusted data assets.

• Promote data democratization while maintaining strong controls and quality standards.

Qualifications:

Experience

• 3+ years of experience in Analytics Engineering, BI Engineering, Data Engineering, Data Warehousing, or related roles.

• Experience in banking, financial services, fintech, or regulated industries is preferred.

• Experience working with modern cloud-based data and analytics platforms.

Technical Skills

• Strong SQL skills and data modeling capability, including dimensional modeling and analytical model design.

• Experience building semantic models, data marts, curated datasets, and business-ready data products.

• Hands-on experience with tools such as Power BI, Microsoft Fabric, dbt, Databricks, Snowflake, BigQuery, or equivalent platforms.

• Understanding of data quality, metadata management, lineage, access control, and governance practices.

AI Tool Fluency - Minimum Requirement

• Minimum hands-on working knowledge of at least one major AI assistant such as ChatGPT, Claude, or Gemini.

• Ability to use AI tools responsibly for data analysis support, SQL generation review, documentation, requirement clarification, test case ideation, and productivity improvement.

• Understanding of prompt writing basics, AI output validation, confidentiality considerations, and limitations of AI-generated answers.

• Curiosity and willingness to adopt Bank X-approved AI tools as part of daily analytics engineering workflow.