Job Details

Job Description

• Apply Link : https://www.mozilor.com/careers/
  
  Required Skills & Experience:
  
  3–5 years of experience in Data Analytics, BI, or Analytics Engineering (preferably in B2B SaaS).
  Strong proficiency in SQL (joins, CTEs, window functions, query optimisation).
  Hands-on experience with ETL tools (e.g., dbt, Airbyte, Fivetran, or Apache Spark) and data warehouses (BigQuery, Redshift, Snowflake, or similar).
  Skilled in Power BI, Looker Studio, or other BI tools for dashboarding and automation.
  Strong communication skills with the ability to explain data concepts to non-technical stakeholders.
  Nice to Have
  
  Experience with Python for automation, transformation, or API integrations.
  Knowledge of data validation frameworks and monitoring tools.
  Familiarity with Mixpanel, Amplitude, or other product analytics platforms.
  Exposure to PLG or freemium SaaS models and experimentation frameworks.
  Familiarity with privacy and compliance requirements (GDPR, CCPA).
  

Job Skills

• Key Responsibilities:
  
  Data Infrastructure Ownership
  Maintain and enhance a unified data architecture.
  Manage data ingestion from key sources such as MySQL, Stripe, Mixpanel, and other product APIs.
  Monitor pipeline health, resolve data discrepancies, and ensure accuracy.
  Manage schema documentation, data lineage, and update transformations as business needs evolve.
  Business Intelligence & Reporting
  Own and maintain dashboards in Power BI, Looker Studio, or Fabric for cross-functional stakeholders.
  Support business reporting across MRR, ARPU, churn, LTV, and funnel performance.
  Build and automate self-serve dashboards for Product, Growth, and Finance.
  Partner with leadership to define KPIs and build high-impact visualisations.
  Product & Behavioural Analytics
  Maintain product tracking setup in Mixpanel (or equivalent), ensuring consistent event taxonomy and validation.
  Collaborate with Product and Engineering to track feature usage, adoption, and retention metrics.
  Ensure alignment between product analytics and revenue data for end-to-end insights.
  Data Governance & QA
  Maintain event taxonomy, naming conventions, and data ownership per domain (Product, Growth, Finance).
  Implement QA checks for key metrics and flag anomalies proactively.
  Ensure compliance with GDPR and privacy-by-design principles in data handling.
  Collaboration & Continuous Improvement
  Partner with Product, Engineering, and Growth teams to identify new data needs and enable experimentation (A/B testing, feature flags).
  Document data processes and contribute to knowledge-sharing across teams.
  Drive best practices for analytics reliability, validation, and reporting consistency.