Senior BI Engineer

Mumzworld is scaling fast, and data is central to our success.

We are looking for a Senior BI Engineer to join our data team and help drive business insights, storytelling, and decision-making through high-quality analytics and reporting.

This is a high-impact role, reporting directly to the Head of Data, and working cross-functionally with business teams, product managers, and engineers to transform data into actionable intelligence.

You will not only deliver robust dashboards and deep-dive analyses but also help define metrics, improve data literacy across the company, and ensure that our analytics layer is consistent, trusted, and scalable.

You will also leverage generative AI tools to boost productivity, streamline reporting workflows, and enhance collaboration.

Key Responsibilities

• Deliver Impactful Insights
  

Build, maintain, and optimize dashboards, reports, and deep-dive analyses to support critical business decisions.

• Create Impact Dashboards with Storytelling
  

Design dashboards that not only show data but tell a clear story — highlighting insights, business implications, and actions.

• Define and Standardize Metrics
  

Work closely with stakeholders to define KPIs and ensure consistency in metrics across business domains.

• Model for Analytics Needs
  

Collaborate with data engineers and modelers to ensure data structures (in bronze, silver, gold layers) are optimized for reporting and analytical needs following medallion architecture principles.

• Drive Business Conversations
  

Translate business questions into clear analytical deliverables; turn data findings into actionable insights and business narratives.

• Ensure Data Quality & Trust
  

Validate data accuracy and drive initiatives to improve data reliability across all reports and dashboards.

• Leverage Gen AI for Productivity
  

Promote the use of Generative AI tools to accelerate report building, automate documentation, and summarize insights faster.

• Advance Data-Driven Culture
  

Conduct workshops, share knowledge, and uplift the organization’s data literacy and self-service capabilities.

• Support Data Science Projects
  

Partner with the data science team to ensure BI foundations support predictive models, experimentation, and advanced analytics initiatives.

What We’re Looking For

• 5+ years of experience in business intelligence, data analysis, or analytics roles.
  

• Expertise in BI tools like Looker, Power BI, or Tableau.
  

• Strong SQL skills to extract, transform, and analyze large datasets.
  

• Solid understanding of data modeling principles (especially star schema and medallion architecture).
  

• Understanding of incremental load vs full load strategies, and a passion for building your own scheduled queries and data refreshes.
  

• Experience working with cloud data warehouses like BigQuery or Snowflake.
  

• Strong business acumen with the ability to translate data into business value.
  

• Experience building self-service datasets, semantic layers, or LookML models is a plus.
  

• Excellent communication skills — able to present complex findings in a clear and actionable way.
  

Nice-to-Have

• E-commerce experience – Familiarity with product, customer, and order data structures.
  
• Experience with dbt Cloud and modern analytics stacks.
  
• Exposure to data governance, catalogs, or metadata management tools.
  
• Experience with GitHub for version control in analytics workflows.
  
• Understanding of privacy, GDPR, and data compliance best practices.
  

Who You Are – Soft Skills & Personality

We’re looking for a curious, business-savvy, and detail-driven BI analyst who thrives in a fast-paced, collaborative environment.

• Structured & Organized – You design with clarity, document your work well, and maintain consistency across reports and analyses.
  
• Collaborative Communicator – You work well with both technical and business stakeholders.
  
• Results-Oriented – You focus on delivering impactful insights that drive business outcomes.
  
• Analytical & Curious – You dig deep into data, question assumptions, and continuously look for improvement opportunities.