Analytics Data Engineer ( CANDIDATES FROM BANKING AND FINANCIAL BACKGROUND IS PREFERRED)

Roles & Responsibilities"-

• Support development of new Midas models (Internal Data model guideline), and periodic recertification of existing models (with DE)
• Support data model bug fixes and RFCs (with DE)
• Provide design, development, and operational support for key company reports and dashboards
• Prototype new metrics to address evolving business needs
• Serve as technical expert for questions about data model usage in downstream analysis
• Own and review code changes to certified metric and dimension definitions
• Manage communication of data model updates and changes with downstream consumers
• Ensure data models are fully documented, and metrics and dimensions have clear descriptions and metadata

What are we looking for in the candidate?

Technical Skills:

• Domain expertise on business metrics and dimensions
• Understands implications of data modeling decisions on key reporting and analysis use cases
• Effectively communicates how technical details of metric computation affect business interpretation and usage
• Expert on metric design practices
• Able to strictly enforce Minerva best practices to maintain data quality
• Evaluates tradeoffs in compute and storage cost in the implementation of different metric and dimension types
• Plans internal metric migrations to mitigate impacts on downstream data consumers
• Ability to quickly ramp-up on Internal data tools and usage patterns
• Able to design systems/processes to organize and maintain team data assets
• Ensures metrics are easily discoverable and accessible across internal data tools
• Can advise internal tools team (Data Platform) on priority end-user needs
• Ability to develop and maintain simple Spark batch data pipelines
• Ability to create and maintain dashboards & reports in Superset (Internal tool) & Tableau

Other requirements:

• Strong multi-tasking & project management skills, Keen sense of prioritization.
• Self-motivated and driven to deliver agreed results on-time.
• Good story-telling & articulation skills ability to convert analytical output into clear, concise, and persuasive insights & recommendations for technical & non-technical audience
• Strong influence and relationship management skills; comfortable interacting across all levels of stakeholders