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The Analytics Engineer is a key member of the Analytics Center of Excellence (ACoE), responsible for designing, building, and maintaining the data foundation that powers business intelligence and analytics solutions across the organization. This role combines and bridges data engineering and data analytics with deep technical expertise in SQL, Python, Power BI, and data integration with strong analytical thinking to ensure reliable, scalable, and high-quality data assets that enable data-driven decision-making for both banking and fintech domains.

Key Responsibilities

1. Business Insight & Decision Support

• Lead advanced ad-hoc and exploratory analysis to answer complex business questions and support executive decision-making.
• Translate analytical insights into clear business actions, recommendations, and risk indicators.
• Identify emerging business opportunities, trends, and risk signals through data patterns.
• Translate high-level reporting and analytical needs from senior stakeholders into precise analytical requirements and data queries.
• Design and maintain reusable SQL scripts, analytical views, and templates to reduce repetitive requests and manual effort.

2. Liaison Between Business & Analytics Teams

• Act as a primary bridge between Business Units and ACoE, ensuring analytical needs are clearly understood and addressed.
• Conduct advanced ad-hoc analysis independently using SQL, Excel, and BI tools, reducing reliance on central analytics teams.
• Provide structured feedback on BI usability, performance, and data gaps to Analytics Engineering and BI teams.

3. Data Quality, Validation & Governance

• Lead data validation and UAT activities for new reports, dashboards, and systems.
• Investigate, validate, and resolve complex data issues raised by business users.
• Ensure consistent application of business definitions, KPIs, and data standards.
• Work closely with data stewards and ACoE to resolve systemic data quality issues.

4. Change Management, Advocacy & Enablement

• Champion ACoE standards and enforce use of certified data assets, actively preventing shadow IT and spreadsheet sprawl.
• Serve as the primary escalation point for Power Users on complex data, governance, or technical challenges.
• Promote data literacy and self-service analytics maturity across business units.
• Gather structured feedback from business users and channel it into ACoE roadmap improvements.

5. Leadership, Mentorship & Value Measurement

• Mentor and coach Analysts and Junior Analysts on analytical thinking, SQL, Power BI, and Excel.
• Lead and sustain a Power User Community of Practice, facilitating knowledge sharing and best practices.
• Define and track value metrics (e.g., reduced ad-hoc requests, increased adoption, decision impact).
• Support prioritization of analytics initiatives with BU leaders and ACoE.

• Degree in quantitative discipline (computer science, mathematics, engineering etc.).
• Advanced SQL skills (query optimization, joins, subqueries, CTEs, stored procedures).
• Strong proficiency in Power BI (DAX, Power Query, modeling, dashboard design).
• Advanced knowledge of Excel (pivot tables, advanced formulas, Power Pivot).
• Experience with data integration, ETL/ELT processes, and new system data acquisition.
• Strong problem-solving and critical-thinking abilities.
• Ability to translate business questions into analytical requirements.
• Experience in performance monitoring, forecasting, and ad-hoc analysis.
• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or related field.
• 3-5+ years of experience in BI, data analysis, or analytics roles.
• Excellent communication skills with the ability to work across business and technical teams.
• Experience in change management or building a new community or program from the ground up