Data Analyst / Analytics Engineer (B2B SaaS)

Data Analyst / Analytics Engineer (B2B SaaS) CookieYes is building a modern, privacy-focused analytics foundation to unify product, marketing, and revenue data. We’re looking for a Data Analyst / Analytics Engineer who can take ownership of CookieYes data infrastructure, ensuring reliability, scalability, and actionable insights across teams.

You’ll implement, maintain and extend data pipelines, warehouse, and BI systems, empowering Product, Growth, and Finance to make confident, data-informed decisions.

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.

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).

                                    If this opportunity aligns with your career goals, kindly share your updated resume with us at careers@mozilor.com