Data Engineering Manager

About the company

The company is transforming workforce development with an AI-powered marketplace of skill-building courses and learning pathways. We help organizations build skills and stay compliant through a high-quality content catalog, seamless LMS/LXP integrations, and advanced capabilities like skills-based curation and multilingual content creation. More than 2,000 companies, including 150+ of the Global 2000, rely on the company to develop the world's most productive and admired workforces.

Learn more: [link for members]

About the Team

The Data Engineering Manager will guide and grow a lean, focused data engineering team. The team’s mission is to build and scale an AI-ready data foundation that enables reliable analytics, operational reporting, governance, enterprise system integrations, and future AI initiatives across the company. This role partners closely with analysts, business leaders, engineering teams, product management, and data consumers company-wide to improve the accessibility, trust, and usability of enterprise data assets.

About the Role

As a Data Engineering Manager I, you will combine direct people management, team stewardship, operational execution, and technical decision-making. You will own the Data Governance & Accessibility program while serving as the managerial and architectural lead responsible for designing scalable data systems, improving pipeline reliability, and enabling analysts through robust, specialized data solutions.

Success in this role requires balancing high-impact people management (1:1s, performance management, career development) with strategic planning, cross-functional stakeholder management, agile process facilitation, and technical leadership.

Core Responsibilities & Management Expectations

People Management & Mentorship

• Direct Supervision: Conduct effective 1:1s, set clear goals, deliver regular performance feedback, and manage career growth for direct reports.

• Engineering Culture: Foster a psychologically safe team environment built on trust, transparency, continuous improvement, and a growth mindset.

• Team Upskilling: Actively mentor engineers in data engineering best practices, design patterns, testing strategies, and operational discipline.

Team Leadership & Process Stewardship

• Delivery & Execution: Act as a team steward, driving execution, managing team velocity, breaking down bottlenecks, and maintaining operational sustainability.

• Agile & Work Management: Facilitate planning, standups, and prioritization; partner with data analysts and business leaders to translate business needs into well-defined, incremental stories.

• Process Critique & Improvement: Regularly evaluate team processes to refine norms and eliminate friction.

Cross-Functional Collaboration & Stakeholder Alignment

• Stakeholder Enablement: Serve as the primary technical contact for analytics and business leaders to ensure data enablement across departments.

• Project Communication: Maintain radical transparency on team roadmaps, risks, delays, and progress.

• Business & Strategy Alignment: Translate complex technical concepts into business terms for cross-functional partners and leadership.

Technical Governance & Architecture Leadership

• AI-Ready Platform Architecture: Direct the design and scale of our Snowflake-based data platform, ingestion architecture, and AI interface layers.

• Enterprise Integrations: Oversee seamless data ingestion from core systems (e.g., Salesforce, HubSpot, NetSuite, Zendesk, Jira, Confluence) into a centralized, queryable source of truth.

• Data Governance & Observability: Establish company-wide standards for data ownership, access management, lineage visibility, testing/validation, and automated pipeline monitoring.

Performance Objectives

Within 30 Days

• Team & Management Foundation: Establish recurring 1:1s with direct reports, assess team dynamics and individual skill sets, and align on individual goals and development paths.

• Stakeholder Mapping: Build working relationships with key cross-functional stakeholders to map out current data dependencies, pain points, and reporting workflows.

• Full Data Ecosystem Audit: Conduct a comprehensive audit of the end-to-end data stack ( Snowflake, Fivetran, dbt, Looker, etc. ) to evaluate cloud spend, pipeline reliability, data transformations, data quality gaps, and constraints for future AI initiatives.

Within 60 Days

• Operational Execution: Refine team operating rhythms (planning, standups, retro) and prioritization processes to improve delivery transparency and reduce operational friction for analytics requests.

• Standards & Quick Wins: Define foundational engineering standards (code review, dbt testing/modeling guidelines, monitoring/alerting) and implement 1–2 quick wins to improve immediate pipeline reliability.

• Architectural Options Drafting: Draft initial proposals for a modernized, cost-effective data architecture across ingestion, transformation, and storage, evaluating trade-offs between current tooling, usage-based pricing, and AI integration requirements.

Within 90 Days

• Architecture Recommendation: Deliver a formal, well-documented recommendation for a modernized data architecture across the entire stack that optimizes tool and infrastructure costs, improves processing efficiency, and provides a scalable foundation for AI solutions.

• Self-Service & Governance: Establish company-wide standards for data ownership, lineage tracking, and access management to promote secure self-service analytics.

• Team Maturity: Demonstrate measurable improvements in delivery consistency, pipeline reliability, analyst trust, and structured team mentorship.

Within 6 Months

• Phase 1 Platform Implementation: Successfully execute the initial phase of the approved architecture recommendation, delivering core, production-ready pipelines and well-documented datasets.

• High-Performing Culture: Build an engineering culture centered on technical excellence, operational discipline, psychological safety, and clear ownership.

• Strategic Value: Position the data engineering function as a proactive, strategic enabler for company-wide AI and data initiatives.

Success in the Role Looks Like

• Empowered Team: Direct reports feel supported, clear on expectations, and are actively growing in their technical and professional skills.

• Trusted Enterprise Data: Analysts across the organization reliably access trusted, well-documented datasets with minimal operational friction.

• Robust Observability: Data pipelines run with high reliability, clear SLAs, and proactive alerting.

• AI-Ready Ecosystem: The enterprise data platform cleanly supports AI/LLM experimentation and plain-language analytics without requiring major re-architecting.

• Strategic Partnership: Stakeholders across the company view the data engineering team as a collaborative, highly effective driver of business value.

You might notice we don’t list a traditional set of requirements or buzzwords here. That’s intentional.

We’re looking for proven examples from your career that show you can build brands, create scalable systems, and drive measurable marketing impact. When you look back a year from now, you’ll know you’ve elevated the company’s brand and strengthened its market presence.

Location : This position can be based anywhere in the US. We operate as a remote-first company and invest in all-company in-person meetings several times a year.

Performance Driven : We're looking for self-starters with a track record of delivering excellent results, but we're highly selective about who we hire. We don't focus on typical job requirements; instead, we're interested in specific examples from your past experiences. All positions can be based anywhere in the US, and require up to 15 days of travel per year, with senior management and leadership teams requiring up to 35 days.

Compensation: The salary for this role range between $180,000 - $208,000  per year, depending on experience. At the company, we offer a comprehensive benefits package to employees upon hire, including professional development, ISOs, health insurance, 401(k) matching, and paid time off. We carefully consider a wide range of compensation factors, relying on market data to determine compensation and consider your specific job family, background, skills, and experience. We prioritize pay transparency, fairness, and equity to create a positive and inclusive work environment, regularly reviewing our compensation practices to align with our values and goals.

Benefits: Benefits include comprehensive medical, dental, and vision coverage, flexible PTO, 401(k) matching, incentive stock options, volunteer time off, Employee Resource Groups, and a generous professional development program with dedicated annual time off for learning and growth.

We use AI. For real. Every team at the company works with AI tools daily, not as a buzzword, but as practice. You'll build fluency that most companies are still talking about adopting, with hands-on training and clear guardrails to experiment responsibly. AI amplifies your creativity and judgment. It doesn't replace them. The skills you build here travel with you.

Equal Employment Opportunity : the company is an Equal Employment Opportunity and Affirmative Action employer that values and welcomes diversity. We do not discriminate on the basis of various legally protected characteristics, including criminal history, and strive to provide reasonable accommodations to qualified individuals with disabilities. We prioritize safety and security and may use your information accordingly, and you can contact us for assistance or accommodations during the job application process.

Pay Transparency : At the company, we prioritize pay transparency, fairness, and equity to create a positive and inclusive work environment, regularly reviewing our compensation practices to align with our values and goals. We provide competitive and fair compensation to our employees based on their skills, experience, and performance.

CPRA (California Candidates): When you submit your application, the company may collect and use your personal information in accordance with our privacy policy and the CPRA. This may include personal details and employment history, and will only be used for employment-related purposes. We may share this information with third-party service providers, but we will not sell it to third parties. If you have any questions or concerns, please contact us, and for more information on your rights under the CPRA, refer to our privacy policy or the California Attorney General's website.

We Care About Your Security: We’ve been made aware of a phishing scam involving individuals impersonating the company recruiters. All legitimate communication from our team will come from [link for members] email addresses. If you receive a suspicious message, please contact us directly at [link for members] Your security matters to us — thank you for staying vigilant