Senior Manager, Analytics Engineering
New
T
ToastEnterprise data
Remote, USFull-TimeManager
SalaryZone A $195,000 — $312,000 USD; Zone B $169,000 — $270,000 USD; Zone C $152,000 — $243,000 USD. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits.
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Job Details
- Experience
- 8+ years experience in Business Intelligence, Analytics, and/or Data Engineering roles; 2+ years experience managing or formally leading a team of analytics or data engineers; 5+ years experience developing data modeling strategies at scale; 4+ years experience developing in dbt
- Required Skills
- SQLBusiness IntelligenceSnowflakeAirflowData engineeringData modelingdbt
Requirements
- Have 8+ years of experience in Business Intelligence, Analytics, and/or Data Engineering roles.
- Have 2+ years of experience managing or formally leading a team of analytics or data engineers.
- Have 5+ years of experience developing data modeling strategies at scale.
- Have 4+ years of experience developing in dbt.
- Be highly proficient in SQL, with a focus on query design and performance.
- Understand the business needs behind data modeling decisions.
- Demonstrate the ability to influence senior stakeholders and drive alignment.
- Be comfortable operating under ambiguity in a fast-paced environment.
- Airflow experience is a nice to have.
- Experience with Sigma, Hex, and/or other BI dashboard tools is a nice to have.
- Experience with cloud-based data warehouses, specifically Snowflake, is a nice to have.
- Python experience is a nice to have.
Responsibilities
- Own the strategy and roadmap for a hub-and-spoke data architecture and drive alignment across domain teams.
- Lead the team building and maintaining the core Analytics layer in the data warehouse.
- Ensure the Analytics layer meets the needs of domain teams building on top of it.
- Set the vision for an AI-ready semantic layer that can extend across business domains, and guide its execution.
- Build, manage, and develop a team of analytics engineers through hiring, coaching, and growth paths.
- Partner with senior business stakeholders and product and engineering leadership to align on analytics priorities.
- Represent EDS’s analytics strategy in cross-functional and leadership forums.
- Partner with data engineering leadership on platform scalability and coherent architecture across teams.
- Provide technical and people leadership, mentorship, and career development to team members.
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