Senior Manager of Data Engineering, Justworks

• As a Sr. Manager, Data Platform Engineering,, how results are achieved is paramount for your success and ultimately results in our success as an organization
• You're a hands-on engineering leader with deep experience building and operating modern data platforms
• You've led teams through scale — evolving architecture, improving reliability, and making hard tradeoffs between speed, cost, and quality
• You're as comfortable reviewing a PR or debugging a pipeline failure as you are setting quarterly roadmap priorities or presenting a platform strategy to senior leadership
• You think in systems - how pipelines, orchestration, governance, and observability connect to produce a trustworthy platform - and you know how to build a team that operates with both craft and urgency
• You develop engineers, set a high technical bar, and create an environment where people grow
• You bring strong opinions grounded in experience with modern PaaS data stack technologies - Snowflake, Fivetran, Airflow, dbt, Estuary - and you've seen what works and what doesn't at scale
• Snowflake is core to how we operate and you should have depth there
• Plans & Aligns - Ensures individual actions support company mission; communicates effectively; understands urgency and plans accordingly
• Balances Stakeholders - Understands internal and external stakeholder requirements, expectations, and needs and acts fairly despite conflicting demands of stakeholders
• Influence and Leadership - fostering a community of knowledge-sharing, collaboration, mentorship, and forward-thinking across the organization
• Manages Complexity - Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problems
• Good Judgment - Pauses before acting; asks questions to fully understand context; applies critical thinking and takes ownership of outcomes
• Teamwork & Communication - Honors diverse thoughts and opinions; leverages unique skills to maximize efficiency
• Skills and Knowledge - the capacity to actively learn and apply specific domain knowledge, know-how, and best practices to continually enhance and improve
• In addition, all Justworkers focus on aligning their behaviors to our core values known as COGIS. It stands for:
• Camaraderie - Day to day you can be seen working together toward a higher purpose. You like to have fun. You’re an active listener, treat people respectfully, and have a strong desire to know and help others
• Openness - Your default is to be open. You're willing to share information, understand other perspectives, and consider new possibilities. You’re curious, ask open questions, and are receptive to thoughts and feedback from others
• Grit - You demonstrate grit by having the courage to commit and persevere. You’re committed, earnest, and dive in to get the job done well with a positive attitude
• Integrity - Simply put, do what you say and say what you'll do. You’re honest and forthright, have a strong moral compass, and strive to match your words with your actions while leading by example
• Simplicity - Be like Einstein: “Everything should be made as simple as possible, but no simpler.”
• You're a builder who applies systems thinking to internal infrastructure. You're comfortable working across a diverse data organization and partnering with leadership to turn fragmented ways of working into scalable, durable systems
• 10+ years of professional experience in data engineering, with at least 5 years working hands-on with modern PaaS data stack technologies (Snowflake, Fivetran, Airflow, dbt, Estuary, or equivalent)
• Deep Snowflake expertise - schema design, query optimization, cost governance, data sharing, and performance tuning at scale
• 5+ years of engineering management experience, including experience managing managers or leading a multi-team engineering organization
• Strong architectural judgment - able to make sound decisions on pipeline design, infrastructure patterns, and platform evolution
• Experience leading a distributed engineering team across multiple workstreams and delivery tracks
• Deep proficiency in SQL and Python; recognized by peers for technical rigor
• Strong expertise with AWS services (S3, Lambda, Fargate, Redshift, Kinesis) and infrastructure-as-code (Terraform, CloudFormation)
• Strong experience with data governance, security, and compliance in a production environment
• Excellent communicator — able to engage technical and non-technical stakeholders, present platform strategy to senior leadership, and translate infrastructure investments into business terms
• Comfortable navigating ambiguity and driving work forward in a fast-moving environment
• Point of view on how AI is changing data platform engineering — both in how the team works and what the platform enables

Desirable

• The Data & Analytics team is Justworks' data and AI center of excellence — a connected set of functions spanning business intelligence, data science, analytics engineering, platform data/ML engineering and AI builders
• We've grown significantly over the last several years and continue to build momentum across the business, leveling up maturity in how we deliver insights, govern data, and enable the company to make better decisions
• You'll find a highly collaborative & diverse group motivated by craft, shared learning, and a genuine commitment to growing our impact for customers while evolving how we work together for our people
• The Data Platform Engineering team sits at the core of this foundation, owning the pipelines, platform infrastructure, and reliability that every other DNA function depends on
• Reporting to the VP of Data & Analytics, you'll lead the data platform organization, setting technical direction, driving operational excellence, and ensuring the platform is reliable, scalable, and built to support the company's growth
• Platform Leadership & Technical Direction:
• Own the technical direction of Justworks' core data platform — pipelines, infrastructure, orchestration, and the standards that keep it trustworthy
• Lead architectural decisions on cloud data infrastructure, balancing scalability, cost, reliability, and security
• Drive operational excellence across the platform — observability, data quality, cost optimization, incident management, and SLAs
• Set and enforce engineering standards — testing, documentation, CI/CD, and code review best practices
• Maintain and evolve infrastructure as code, ensuring the platform is auditable, repeatable, and resilient
• Team Leadership & Development:
• Lead and develop a team of data engineers, including direct line managers and individual contributors at various levels
• Set a high bar for engineering craft — mentor engineers, conduct architecture reviews, and foster a culture of continuous improvement
• Recruit and hire high-caliber data engineers as the platform team grows
• Create an environment where engineers develop their skills, take ownership, and do the best work of their careers
• Cross-Functional Partnership & Delivery:
• Partner with DNA functional teams (e.g. Analytics Engineering, BI, Data Science) and distributed Data Engineering teams to ensure the platform serves the full breadth of org needs
• Collaborate with other engineering teams to align on data contracts, security, compliance, and shared infrastructure
• Drive planning processes that connect platform priorities to DNA's overall strategy and enterprise OKRs
• Technologies Used:
• Languages: Python, SQL, Terraform
• Data & Analytics: Snowflake, dbt, Fivetran
• Streaming & CDC: Estuary
• Workflow Orchestration: Airflow, MWAA
• Cloud: AWS (S3, Lambda, Fargate, Redshift, Kinesis, Step Functions, EventBridge)
• Observability & Monitoring: Datadog
• CI/CD: CircleCI, GitHub Actions