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Business Intelligence II-SUPPORT SERVICES-Data & Analytics - In House Engin at Kotak Mahindra Bank

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

21 Sep, 26

Salary

0.0

Posted On

23 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

BI Reporting, Dashboard Development, Data Modeling, Semantic Layers, Star Schema, Data Engineering, BI Architecture, SDLC, CI/CD, ETL/ELT Pipelines, Data Marts, UX Design, Data Governance, KPI Translation, Automated Testing, Observability

Industry

Banking

Description

Please find the JD as below, grade would be M5: 1. BI Reporting, Dashboards & Analytics Enablement • Lead end to end development of executive, regulatory, and operational dashboards that align with business objectives and MIS/reporting needs. • Design and build semantic layers, star schema/denormalized data models, and analytics friendly consumption layers. • Translate business KPIs into intuitive, high-performance dashboards; ensure clarity, visual usability, and stakeholder alignment. • Define organization wide standards for visualization, UX, storytelling, and dashboard governance to drive consistency across teams. • Implement automated checks, validations, reconciliations, and alerting to ensure accuracy, timeliness, and availability of BI outputs. 2. Data Engineering & BI Architecture • Architect and oversee large scale BI data solutions—including data marts, reporting layers, and analytical datasets. • Apply strong SDLC practices: version control, CI/CD, automated testing, observability, documentation, and security. • Partner with data engineering teams to maintain freshness SLAs and ensure reliable ETL/ELT pipelines powering BI-LAYERS. • Optimize data pipelines and consumption layers for scale, performance, and cost efficiency.

Responsibilities

Lead the end-to-end development of executive and operational dashboards while defining organization-wide visualization and governance standards. Architect large-scale BI data solutions and optimize data pipelines to ensure high performance and reliability.