Senior Manager, Analytics Engineering
United States
Applications have closed
DeleteMe is seeking an accomplished and hands-on Senior Manager of Analytics Engineering to lead our Analytics Engineering team. This team plays a critical role in shaping our data infrastructure, ensuring seamless data integration, robust data modeling, and efficient data pipelines. The Senior Manager will drive the vision for our analytics architecture, focusing on business-critical outcomes and long-term scalability. Leveraging modern data warehousing technologies like Snowflake, dbt Enterprise, and integration tools such as Fivetran and Hightouch on AWS, this leader will ensure that our data systems support both immediate business needs and future growth.
Requirements
- Team Leadership & Collaboration:
- Staff, lead, and mentor a team of 2 Analytics Engineers, fostering a collaborative and growth-oriented environment .Partner with BI & Analytics, Business Systems, Operations, and Product teams to ensure analytics solutions align with business objectives and deliver actionable insights. Manage day-to-day operations, ensuring the team provides high-quality, reliable data models and pipelines to support decision-making across the organization. Drive a culture of continuous improvement, ensuring team members are up-to-date with the latest technologies, methodologies, and best practices in analytics engineering.
- Data Modeling & Integration: Oversee the development and maintenance of well-documented, high-performance data models in dbt Enterprise, designed to meet the business needs of key stakeholders. Ensure seamless integration of data from various sources, including internal platforms and third-party systems like Stripe, NetSuite, Maxio, Salesforce, ZoomInfo, Outreach, HubSpot, Rippling, and Chorus, using tools like Fivetran and Hightouch. Lead efforts to optimize data flows between systems and the data warehouse (Snowflake), ensuring scalability and reliability of the data infrastructure.
- Pipeline Development & Optimization:Ensure that data pipelines are built to be scalable, efficient, and resilient, supporting both real-time and batch processing needs.Implement and maintain DevOps/CICD practices to improve the speed and reliability of data pipeline deployment.
- Data Quality, Governance, and Stewardship:Partner with our Security team to implement and enforce data quality standards and governance practices.Establish data validation, cleansing, and monitoring processes to maintain high data quality and accuracy.Promote adopting data stewardship practices, ensuring that data is managed as a valuable asset across departments with consistent definitions and usage standards.
- Qualifications:Bachelor's degree in Data Engineering, Analytics, Computer Science, or a related field. Master's degree is a plus.6+ years of experience in analytics engineering or data engineering, with at least 2 years in a leadership or management role. Strong technical experience with data warehousing (Snowflake), data modeling (dbt Enterprise), and data integration tools (Fivetran, Hightouch).Hands-on experience with building and optimizing data pipelines in cloud environments (AWS preferred).Proven experience in data governance, data quality management, and implementing data stewardship programs.Strong project management skills, with the ability to balance short-term tactical needs with long-term strategic objectives.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
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Tags: Architecture AWS Computer Science Data governance Data pipelines Data quality Data warehouse Data Warehousing dbt DevOps Engineering FiveTran HubSpot Pipelines Salesforce Security Snowflake
Region:
North America
Country:
United States
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