Senior Manager, Analytics Engineering
About The Position
We're Redis. We built the product that runs the fast apps our world runs on. (If you checked the weather, used your credit card, or looked at your flight status online today, you’re welcome.) At Redis, you’ll work with the fastest, simplest technology in the business—whether you’re building it, telling its story, or selling it to our 10,000+ worldwide customers. We’re creating a faster world with simpler experiences. You in? Senior Manager, Analytics Engineering Define/execute strategic roadmap for analytics engineering initiatives; design, develop, maintain robust/ scalable data pipelines to support reporting, analytics/data science needs; use BI Platform Architecture/Analytics Enablement, scalable data pipelines, Agile Methodologies, KPI & Metric Designs; perform ETL/Reporting (Matillion, DBT, Snowflake, Boomi, Tableau, AWS S3, Lambda, SQL, PL/SQL); work with tools (Salesforce, NetSuite, Marketo, Greenhouse, Clari, PeopleAI, Jira, Coupa, ServiceNow, SAP SuccessFactors, Google Analytics, Xactly, Github); ensure data quality, accuracy/ consistency across all data assets; collaborate with product, engineering, go-to-market, business stakeholders to understand data requirements/deliver impactful solutions; implement best practices for data governance, security, compliance; evaluate/recommend new tools/technologies to enhance data platform capabilities; design/implement processes to support self-service analytics/data democratization; support executive reporting/board-level presentations with high-quality, reliable data; drive continuous improvement in data engineering processes/methodologies; serve as company-wide expert on Redis’ internal data; review analytics needs of business/design; build Redis’ analytics data warehouse; work with team of data science professionals/cross-functional teams to identify business opportunities; build scalable data solutions; build high-performing analytics engineering team to create analytics-friendly, scalable data infrastructure for entire company; introduce processes/ documentation that accelerate pace of analytics work; enforce software engineering best practices to analytics code (version control, code reviews); manage documentation/definitions; create clean, reusable datasets from raw data; manage pipeline orchestration; lead efforts in customizing data integration; standardize data management practices; detect data quality issues/root causes; design, build/maintain all aspects of analytics data warehouse; design/develop applications for descriptive, prescriptive/predictive analysis for valuable insights from available data; lead, mentor, grow team of analytics engineers; and gather/document business and system requirements. This is a telecommuting position with remote benefit from various unanticipated locations throughout the U.S.
Requirements
- Master’s degree or foreign equivalent in Computer Science, Applied Computer Science, or Computer Engineering plus 2 years experience.
- Experience to include using BI Platform Architecture/Analytics Enablement, scalable data pipelines, Agile Methodologies, KPI & Metric Designs
- Performing ETL/Reporting (Matillion, DBT, Snowflake, Boomi, Tableau, AWS S3, Lambda, SQL, PL/SQL)
- Working with tools (Salesforce, NetSuite, Marketo, Greenhouse, Clari, PeopleAI, Jira, Coupa, ServiceNow, SAP SuccessFactors, Google Analytics, Xactly, Github)
Responsibilities
- Define/execute strategic roadmap for analytics engineering initiatives
- Design, develop, maintain robust/ scalable data pipelines to support reporting, analytics/data science needs
- Use BI Platform Architecture/Analytics Enablement, scalable data pipelines, Agile Methodologies, KPI & Metric Designs
- Perform ETL/Reporting (Matillion, DBT, Snowflake, Boomi, Tableau, AWS S3, Lambda, SQL, PL/SQL)
- Work with tools (Salesforce, NetSuite, Marketo, Greenhouse, Clari, PeopleAI, Jira, Coupa, ServiceNow, SAP SuccessFactors, Google Analytics, Xactly, Github)
- Ensure data quality, accuracy/ consistency across all data assets
- Collaborate with product, engineering, go-to-market, business stakeholders to understand data requirements/deliver impactful solutions
- Implement best practices for data governance, security, compliance
- Evaluate/recommend new tools/technologies to enhance data platform capabilities
- Design/implement processes to support self-service analytics/data democratization
- Support executive reporting/board-level presentations with high-quality, reliable data
- Drive continuous improvement in data engineering processes/methodologies
- Serve as company-wide expert on Redis’ internal data
- Review analytics needs of business/design
- Build Redis’ analytics data warehouse
- Work with team of data science professionals/cross-functional teams to identify business opportunities
- Build scalable data solutions
- Build high-performing analytics engineering team to create analytics-friendly, scalable data infrastructure for entire company
- Introduce processes/ documentation that accelerate pace of analytics work
- Enforce software engineering best practices to analytics code (version control, code reviews)
- Manage documentation/definitions
- Create clean, reusable datasets from raw data
- Manage pipeline orchestration
- Lead efforts in customizing data integration
- Standardize data management practices
- Detect data quality issues/root causes
- Design, build/maintain all aspects of analytics data warehouse
- Design/develop applications for descriptive, prescriptive/predictive analysis for valuable insights from available data
- Lead, mentor, grow team of analytics engineers
- Gather/document business and system requirements
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What This Job Offers
Job Type
Full-time
Career Level
Manager
