Senior Manager Data Engineer

Third Sector Intelligence is a software (SaaS) company that helps governments, nonprofits, and philanthropies use data to improve the lives of children. They are seeking a Senior Manager, Data Engineer to oversee the data engineering team, ensuring timely and quality engineering deliverables while collaborating with cross-functional teams and providing mentorship to team members.

Responsibilities:

• Oversee the planning, execution, and delivery of data engineering projects, ensuring alignment of goals, timelines, and quality standards using agile development/delivery methodologies
• Partner directly with the CTO to shape and evolve the long-term data architecture and engineering roadmap, including the adoption of innovative technologies such as generative AI to accelerate development cycles
• Recognize and act on opportunities to convert bespoke or experimental pipelines and algorithms into standardized, reusable components that drive efficiency and scalability across the organization
• Lead the team through the design, documentation, and implementation of standardization initiatives, ensuring consistent practices and high-quality deliverables
• Work closely with senior management to align data engineering initiatives with business objectives and contribute to the engineering strategy
• Effectively allocate resources to ensure optimal project delivery and team productivity. Manage costs and identify waste
• Provide technical leadership and guidance to team members, staying informed of industry trends and ensuring team uses appropriate technologies and best practices
• Conduct regular reviews to ensure code quality, adherence to code standards and implementation of best practices
• Identify potential risks in project and implement risk mitigation strategies to ensure project delivery
• Collaborate cross-functionally across the organization to ensure cohesive and integrated approach to product development and delivery
• Lead and manage data engineer team, providing guidance and mentorship, set performance goals, provide feedback and coaching, recruit, and implement development plans to foster an innovative, AI-aware team culture
• Contribute directly to the codebase, as needed

Requirements:

• 7+ years of progressive experience in data engineering, including hands-on pipeline development and architecture design
• 3+ years leading engineering teams within a SaaS or high-growth technology environment using agile methodologies
• Bachelor's degree in computer science, information technology or related field
• Expertise in Python and SQL for data transformation and modeling
• Experience building scalable pipelines using cloud-native data services
• Demonstrated experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Databricks, Azure)
• Strong understanding of CI/CD and source control best practices
• Experience implementing data quality, observability, and governance standards
• Experience working with complex, sensitive, or regulated datasets
• Comfort navigating compliance and security standards such as FERPA, SOC 2, NIST, etc
• Fluency in applying generative AI tools and techniques to accelerate development, prototype solutions, and optimize workflows
• Proven track record of identifying and executing standardization opportunities for custom pipelines and algorithms, improving maintainability and reducing duplication