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Data Analyst

Jobslink Inc
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Data Analyst (Analytics & BI)

Location: San Diego, CA or Remote (U.S.)

Team: Data & Analytics | Type: Full-time

 

About the role

We’re seeking a Data Analyst who turns raw data into clear, decision-ready insights. You’ll own KPI definitions, build interactive dashboards, run exploratory and statistical analyses, and partner with stakeholders to drive measurable outcomes across operations, marketing, and product.

 

What you’ll do

1) Translate business questions into analysis plans; define metrics and build reusable semantic layers.

2) Create executive and team dashboards in Power BI and Tableau; deliver self-serve reporting and ad-hoc analyses.

3)Able to work robust SQL across Snowflake/Redshift/BigQuery and SQL Server/PostgreSQL; optimize queries and data models.

4) Perform EDA, cohort analyses, forecasting, and A/B test readouts; clearly communicate findings to technical/non-technical audiences.

5) Build light ETL/ELT data prep in Python (Pandas) and SQL; ensure accuracy, freshness, and lineage documentation.

6) Implement data quality checks and validation scripts; reduce reporting errors and improve reliability.

7) Partner with engineers and business owners to prioritize analytics roadmaps and measure impact.

 

Minimum qualifications:

1) 2+ years in data analytics or BI with a track record of delivering dashboards and analyses that influence decisions.

2) Proficient in SQL (joins, window functions, CTEs) and Python (Pandas, NumPy); strong Excel.

3) Hands-on with Power BI and/or Tableau (KPI design, drill-downs, DAX/calculations, storytelling).

4) Working knowledge of data warehousing concepts and ELT best practices.

5) Solid grasp of statistics (hypothesis testing, regression, time-series basics) and experiment analysis.

6) Clear, concise communication and stakeholder management skills.

 

Preferred qualifications:

1) Exposure to Snowflake, Redshift, BigQuery, AWS (S3/Glue/Lambda) or Azure.

2) Experience with Airflow, Spark/PySpark, Alteryx, or SAS for data prep/orchestration.

3) Familiarity with ML-assisted analytics (scikit-learn, TensorFlow/PyTorch), NLP (NLTK), or SageMaker.

4) Reporting tools beyond BI (e.g., SSRS) and monitoring (Grafana).