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Mid-level generalist data role with broad stack and common title increases candidate pool and competition.
Technical skills are transferable, but product-development and production pipeline experience increases industry specificity.
Multiple explicit years requirements, mandatory techs (Power BI, SQL, Python, cloud) and production project counts.
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Analyze complex datasets using advanced statistical methods to generate insights and data-driven recommendations for business problems.
Design, develop, deploy, and maintain data transformation components, orchestration pipelines, and data visualization dashboards in production environments.
Collaborate with engineers, product teams, and stakeholders to align data strategy with business objectives and provide technical support and reviews to junior data scientists.
Bachelor’s or Master’s degree in quantitative fields such as Statistics, Computer Science, or Engineering.
3+ years of experience as a Senior Data Analyst in a product development company.
5+ years of experience developing, deploying, and maintaining data transformation pipelines and visualization dashboards (Power BI or Qlik Sense) in production (5+ projects).
3+ years of proficiency in Python, PySpark, Java programming; strong hands-on SQL skills; 3+ years cloud infrastructure experience; 3+ years experience with code version control tools (git, GitHub, GitLab).
Experienced in leading analytics projects from solution design to production deployment with focus on modular, scalable, and reusable data pipelines.
Skilled in communicating complex technical DT pipelines and findings effectively to non-technical stakeholders.
Demonstrated ability to collaborate cross-functionally with engineers, product teams, and business stakeholders, and provide mentorship/technical support to junior data scientists.