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Revolution Supply Co.

Sr Data Analyst

This role is for a Sr Data Analyst focused on AWS migration and cloud data warehousing, requiring 5+ years in e-commerce data analysis. Contract length is permanent, with remote work. Key skills include SQL, AWS services, and data visualization.
🌎 Country
United States
🏝️ Location
Remote
πŸ“„ Contract
Full-time
πŸͺœ Seniority
Mid-Senior level
πŸ’° Range
Unknown
πŸ’± Currency
$ USD
πŸ’Έ Pay
Unknown
πŸ—“οΈ Discovered
August 27, 2025
πŸ“ Location detailed
Santa Ana, CA
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🧠 Skills
#Magento
Role description
Job Title: Sr Data Analyst – AWS Migration & Cloud Data Warehouse Location: Remote / [Client Location] Type: Full-Time / Contract Department: Data & Analytics Position Summary: We are seeking a results-driven Sr Data Analyst to support both the migration of data infrastructure from Microsoft Azure to AWS and the ongoing analytics and reporting needs in the post-migration cloud environment. Your experience will include at least 5 years in a product rich environment analyzing e-commerce, forecasting and inventory data for key decision makers. This role is critical to ensuring data quality, business continuity, and analytic value throughout the migration lifecycle and beyond. The Data Analyst will work closely with AWS engineers, business stakeholders, and analytics teams to design, validate, and operationalize data workflows in a modern AWS-based architecture. Key Responsibilities: Pre-Migration (Assessment and Transition Support): β€’ Analyze and document current-state data sources (e.g., Dynamics 365 BC, SQL Server, Access, Magento, PIM, Repricer, APIs). β€’ Conduct data profiling and quality assessments to inform migration strategies. β€’ Collaborate with engineers and architects to support data mapping, transformation, and validation processes during migration. β€’ Help define and document performance, compliance, and availability requirements for datasets being moved to AWS. β€’ Support migration testing and cutover planning for reporting and analytic workloads. Post-Migration (AWS Data Warehouse Enablement): β€’ Perform ongoing data validation, reconciliation, and quality monitoring across S3, Redshift, Glue, and other AWS data services. β€’ Develop and maintain dashboards, visualizations, and reports using Amazon QuickSight or equivalent BI tools. β€’ Translate business questions into data-driven analyses and deliver actionable insights across sales, operations, and e-commerce domains. β€’ Support business stakeholders with ad hoc data needs and self-service analytics enablement. β€’ Partner with ML/GenAI teams to prepare and validate data sets for AI/ML models, and assist in measuring model outputs. β€’ Document data dictionaries, business logic, and data lineage to ensure transparent and auditable reporting. β€’ Contribute to ongoing data governance, security, and cost optimization practices in AWS. Required Qualifications: β€’ Bachelor’s degree in Data Science, Computer Science, Information Systems, or related field. β€’ 3+ years of experience in a Data Analyst or BI Analyst role supporting cloud-based data platforms. β€’ Proficiency in SQL and data manipulation across relational and cloud-based data stores (e.g., Redshift, SQL Server, Access). β€’ Experience working with API-driven data sources and unstructured data. β€’ Familiarity with AWS data services such as S3, Glue, Redshift, and QuickSight. β€’ Strong data profiling, visualization, and problem-solving skills. β€’ Ability to translate business needs into technical data requirements and outputs. Preferred Qualifications: β€’ Experience with data migration projects, particularly from Azure to AWS. β€’ Knowledge of tools like Athena, Python (Pandas), or dbt for data transformation and exploration. β€’ Understanding of data warehouse design, dimensional modeling, and cost-efficient architecture patterns. β€’ Exposure to Amazon seller channel data, e-commerce analytics, or ERP reporting. β€’ Familiarity with GenAI or ML model support workflows is a plus. Tools & Technologies: β€’ AWS: Redshift, S3, Glue, Athena, QuickSight β€’ SQL: Microsoft SQL Server, Access, Jet Cubes β€’ APIs: Reason Automation, Stackline, Sales Layer, Keepa β€’ Data Wrangling: Excel, Python, Pandas β€’ Collaboration: Jira, Confluence, Git