Data Analyst (Catalog Analyst)

Remote, USA Full-time Posted 2025-03-08

Intermediate Data Analyst Apex Systems is a global IT services provider, and our staffing practice has an opening in the Online Retail space for Data Analysts with strong experience in investigative data analysis that results in growth combined with experience in SQL, databases of a terabyte or more and optimum queries to place at our client. Client: Ecommerce Shopping Technology Enterprise... Terms: 12 months with possibility of extension Start date: ASAP. Office Location: 100% remote (within Canada) Must have: Data Analyst with some data engineer skills (data pipelines) Visualization software - mode or tableau Python or R eCommerce or Retail background is a nice to have Job description: Assess/query large datasets to determine impactful trends within our business. Interpret data trends and patterns. Correlate to actionable insights. Work closely with cross-functional partners to communicate discovered trends, resolve data issues, troubleshooting and analysis, and bug fixes Develop reports and presentations for various business stakeholders Work with teams across the Company on data quality and availability Develop new frameworks to collect data including automated data collection Collaborate with Data Warehouse and Engineering teams to manage relevant datasets within the Company. Data Analysis and Interpretation: Collect, analyze, and interpret data to identify trends and patterns affecting our Ads Taxonomy table. Translate data findings into actionable insights and recommendations for the core team. Data Collection and Strategy: Develop and implement effective data collection systems and strategies to support automation and integration projects. Ensure data accuracy, availability, integrity and reliability for various initiatives. Cross-Functional Collaboration: Collaborate with teams across different functions to support entity and taxonomy realignments. Identify process improvement opportunities and provide regular recommendations to enhance data-related processes. SQL Expertise: Utilize efficient SQL writing and querying techniques to troubleshoot issues directly within the Snowflake data warehouse. Optimize queries for performance and maintainability. Data Workflows and Insights: Work with data tools including SQL and Tableau to automate data workflows. Build meaningful insights through data visualizations, standardized reports, and dashboards for ad-hoc analyses. ABOUT YOU Experience in a quantitative role at a product company A high level of organization and attention to detail Familiarity with Database interface tools, SQL, and Programming concepts Relevant experience within the Retail space along Eagerness to learn, flexibility to pivot when needed, savviness to navigate and thrive in a dynamic environment, and a growth mindset needed to build a successful team and company. Experience with Data mapping, Data architecture, Data integration, ETL, and working on large datasets Requirements: Bachelor?s degree or equivalent work experience in a relevant business/domain. Hands-on experience with SQL, Data Manipulation, and Data Analysis. Experience working with bad data turning it into a story Ability to work independently as an individual contributor, taking ownership of assigned tasks/projects. Capable of collaborating effectively in team environments, especially on large/complex projects. Flexibility to adapt to changing project requirements and reprioritizations. Proficiency in documentation, creating and accepting handovers, and effectively managing change/release communications. Strong verbal and written communication skills Exposure to working with large data platforms and handling sizable datasets is a plus. Snowflake, Cassandra or Vertica Mode/Tableau (Data Visualization) comfortability working with raw/ad data and the ability to create a story out of it. 2 years of experience applying Python (NumPy, Pandas, Other common libraries) programming to solve business challenges. Scripting/development experience with Python, including working with Google APIs, building data pipelines, authentication, file handling, and raw data manipulation is a plus

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