Senior Manager, Data Engineering

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. 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.

Responsibilities

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; 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; 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

Requirements

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

Nice to have

Experience building data platforms that support ML/AI workloads (feature stores, model pipelines, vector stores); Background in a regulated or compliance-sensitive environment (fintech, HR tech, healthcare); Experience with streaming/CDC technologies (Estuary, Kafka, Debezium)

Benefits

welcoming and casual environment; great benefits; wellness program offerings; company retreats; ability to interact with and learn from leaders in the startup community