Senior Manager, Data Engineering

Justworks•New York, NY

16h•$240,000 - $310,000•Hybrid

About The Position

The Data & Analytics team is Justworks' data and AI center of excellence, encompassing business intelligence, data science, analytics engineering, platform data/ML engineering, and AI builders. The Data Platform Engineering team is central to this foundation, responsible for the pipelines, platform infrastructure, and reliability that all other Data & Analytics functions depend on. This role involves leading the data platform organization, setting technical direction, driving operational excellence, and ensuring the platform is reliable, scalable, and built to support company growth. The ideal candidate is a hands-on engineering leader with extensive experience building and operating modern data platforms, leading teams through scaling challenges, and improving architecture, reliability, and making trade-offs between speed, cost, and quality. They should be comfortable with both technical tasks like reviewing code and debugging, as well as strategic responsibilities like setting roadmaps and presenting platform strategies to senior leadership. A systems-thinking approach to data pipelines, orchestration, governance, and observability is crucial, along with the ability to build and lead a team that operates with both craft and urgency. Strong opinions grounded in experience with modern PaaS data stack technologies like Snowflake, Fivetran, Airflow, dbt, and Estuary are expected, with a particular emphasis on Snowflake expertise.

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 Haves

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)

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