Associate Data Analyst
Listed on 2026-08-04
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IT/Tech
Data Analyst, Data Engineering
Seattle, WA
701 Pike St
Seattle, WA 98101, USA
Seattle, WA
701 Pike St
Seattle, WA 98101, USA
San Francisco, CA
77 Geary St
5th Floor Office 665
San Francisco, CA 94108, USA
San Francisco, CA
77 Geary St
5th Floor Office 665
San Francisco, CA 94108, USA
Atlanta, GA
990 Hammond Drive
Suite 500
Atlanta, GA 30328, USA
Atlanta, GA
990 Hammond Drive
Suite 500
Atlanta, GA 30328, USA
Chicago, IL
500 W Madison St
Suite 3105
Chicago, IL 60661, USA
Chicago, IL
500 W Madison St
Suite 3105
Chicago, IL 60661, USA
New York City, NY
1350 Broadway
#2000
New York City, NY 10018, USA
New York City, NY
1350 Broadway
#2000
New York City, NY 10018, USA
The Associate Data Analyst position performs data analytics for informed decision making, dashboards, report generation and overall project support. This role supports and contributes to organizational success by supporting the delivery of high-quality data solutions. Work is performed under general supervision with guidance provided for complex issues.
Responsibilities- Proactively gather data from diverse internal systems (e.g., CRM platforms, ERP systems, operational databases) and external sources (e.g., public datasets, APIs, third-party vendors, customer surveys).
- Apply robust data cleaning techniques such as handling missing values, correcting data types, removing duplicates, and standardizing formats to ensure high data quality.
- Validate data accuracy by cross-referencing with source systems, applying logic checks, and collaborating with domain experts to confirm assumptions.
- Organize raw data into structured formats—such as data tables, CSV files, or relational databases—making it accessible and ready for analysis by analysts, data scientists, and business stakeholders.
- Conductexploratorydata analysis using statistical techniques (e.g., regression, clustering, hypothesis testing) to uncover hidden patterns, anomalies, and relationships within datasets.
- Visualize trends over time, segment customer behavior, and identify key performance drivers using tools like matplotlib, seaborn, or built-in Excel charts.
- Translate analytical findings into actionable insights that support strategic initiatives such as market expansion, product optimization, or customer retention.
- Respond to data-related inquiries from business units by investigating root causes, validating assumptions, and delivering clear, data-backed answers.
- Design and build dynamic dashboards that track KPIs, operational metrics, and business performance using visualization tools like Tableau, Power BI, or Excel.
- Write efficient SQL queries to extract, join, filter, and aggregate data from relational databases such as MySQL, PostgreSQL, or Microsoft SQL Server.
- Leverage programming languages like Python or R to automate data workflows, perform advanced statistical analysis, and build custom data pipelines.
- Collaborate with cross-functional teams—including marketing, product, finance, and operations—to understand their goals and translate them into data requirements.
- Maintain detailed documentation of data sources, definitions, transformation logic, and business rules to ensure transparency and consistency across reports.
- Monitor data integrity by setting up validation checks, reconciling discrepancies, and working with IT or engineering teams to resolve issues.
- Help standardize procedures for data handling, reporting, and analysis by creating templates, SOPs, and training materials for team members.
- Flexibility to adapt and execute various additional assignments based on evolving needs.
- May provide mentorship, guidance, support, and knowledge‑sharing to help less experienced team members develop their skills and grow within their roles.
- Proficiency in SQL for data extraction, transformation, and analysis
- Advanced Excel and Google Sheets skills, including pivot tables and complex formulas
- Experience with data visualization tools such as Tableau, Power BI, or Excel dashboards
- Strong analytical skills with knowledge of statistical methods (e.g., regression, clustering)
- Ability to perform exploratory data analysis and identify actionable insights
- Familiarity with Python or R for data manipulation and visualization (preferred)
- Skilled in…
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