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.
- Conduct exploratory data 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.
Mentorship - May provide mentorship, guidance, support, and knowledge-sharing to help less experienced team members develop their skills and grow within their roles.
Skills and Competencies - 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 cleaning, validating, and transforming large datasets
- Excellent communication skills for presenting data to non-technical stakeholders
- Collaborative mindset with experience working across departments
- Detail-oriented with a focus on data accuracy and consistency
- Knowledge of data governance, metadata management, and quality assurance practices
- Understanding of data privacy and compliance standards (e.g., GDPR, CCPA)
- Ability to identify process inefficiencies and recommend improvements
- Experience supporting senior analysts with modeling, forecasting, and reporting
Experience - Typically, a minimum of 2 years' related work experience in Data Analytics or a related field is required.
Education - A bachelor's degree in a quantitative field (e.g., Mathematics, Statistics, Economics, Computer Science, or related discipline) is required.
Salary Range: The anticipated starting pay range for this position is based on the employee's primary work location and may be more or less depending upon skills, experience, and education. These ranges may be modified in the future.
Location A:
$71,000 - $96,000
Location B:
$78,000 - $106,000
Location C:
$85,000 - $115,000
You can view which BC location applies to you here. If you have any questions, please speak with your Recruiter.
Benefits and Other Compensation: We provide a comprehensive benefits package that promotes employee health, performance, and success which includes medical, dental, vision, short and long-term disability, life insurance, an employee assistance program, paid time off and parental leave, paid holidays, 401(k) retirement savings plan with employer match, performance-based bonus eligibility, employee referral bonuses, tuition reimbursement, pet insurance and long-term care insurance. Click here to see our full list of benefits.
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