Data Analyst

Client of Stellar Hunters

We are seeking a skilled and detail-oriented Data Analyst to join our team. The successful candidate will work closely with Product, Engineering, and Business teams to transform data into actionable insights that inform product decisions, improve operations, and support strategic initiatives. This role requires strong experience in data analysis, SQL, visualization, and effective communication of findings to technical and non-technical stakeholders.

Key Responsibilities

Data Analysis & Insight Generation

• Collect, clean, and analyze structured and unstructured data from multiple sources to support product, marketing, and operations teams.

• Develop and maintain reports and dashboards that communicate key performance indicators (KPIs), trends, and anomalies.

• Perform exploratory data analysis and root-cause investigations to answer business questions and recommend data-driven actions.

Data Modeling & Pipeline Collaboration

• Collaborate with Data Engineering to define data requirements, improve ETL/ELT processes, and ensure data quality and consistency.

• Design and validate data models and metrics to ensure reliable and repeatable analyses across teams.

• Document data sources, transformation logic, and metric definitions to promote transparency and reproducibility.

Reporting, Visualization & Communication

• Create clear, effective visualizations and presentations that communicate insights, trade-offs, and recommendations to stakeholders.

• Partner with Product and Business teams to translate analytic results into prioritized roadmap items and operational improvements.

• Provide ad-hoc analyses and respond to data requests with well-documented methodologies and reproducible code.

Testing, Measurement & Experimentation

• Support experiment design, implementation, and analysis (A/B testing), including metric selection, power calculations, and interpretation of results.

• Define and track success metrics for new features and product launches to measure impact and guide iteration.

• Implement monitoring to detect data drift, metric regressions, and pipeline failures impacting business reporting.

Documentation, Governance & Collaboration

• Maintain thorough documentation of analyses, dashboards, data dictionaries, and standard operating procedures.

• Advocate for data governance best practices, including access controls, lineage tracking, and consistent metric definitions.

• Mentor colleagues on data literacy and partner across teams to embed analytics into decision-making processes.