VP, Data Engineering

Confido•New York, NY

2d•$300,000 - $350,000

About The Position

Confido is hiring a VP of Data Engineering to take ownership of data across the company, from ingestion and storage through modeling and reporting. Data supports customer-facing reports, internal dashboards, and day-to-day decisions, and currently exists in multiple places with distributed ownership. The VP will establish a single, trusted approach to data and will manage the Senior Analytics Engineer initially, building and leading the data organization as the company grows. The role begins hands-on, including writing SQL, reviewing pull requests, and building systems. Over time, the VP will devote more attention to hiring, setting direction, and working with the leadership team. The VP will set the data roadmap, make technical decisions, define team standards, and partner with Engineering, Product, Operations, and Customer teams to determine data needs. Success means clear ownership of data, trusted and accessible numbers, documented sources, more reliable pipelines, early detection of issues, consistent definitions across internal and customer-facing reports, and a growing team with clear structure, standards, and plans for its next stage.

Requirements

10 or more years of experience in data engineering, analytics engineering, or a similar field.
4 or more years of experience leading data teams.
Experience owning data end to end, from ingestion through reporting.
Experience building a data function from an early-stage or messy state, growing the team, and keeping it running.
Strong SQL and data modeling skills.
Experience with Snowflake, dbt, Airflow, Dagster, or similar tools.
Experience hiring effectively, including hiring people senior to the team's initial level.
Ability to translate broad requests for better data into a plan and defend that plan in leadership discussions.
Comfort working hands-on initially and stepping back as the team grows.

Responsibilities

Own data ingestion from product databases, event tracking, and third-party tools, including ingestion frequency and responses to source changes or failures.
Own warehouse design, orchestration, data pipelines, underlying infrastructure, and associated costs.
Establish core data models and metric definitions used across the company.
Own internal dashboards and business intelligence, as well as the data behind customer-facing reports.
Establish data quality and governance practices, including testing, monitoring, access controls, and data privacy.
Manage the Senior Analytics Engineer and build and lead the data organization, including determining hiring needs, conducting interviews, and developing team members.
Set the data roadmap and explain trade-offs to company leadership and employees.
Make technical decisions on architecture, tooling, and whether to build or buy.
Collaborate with Engineering, Product, Operations, and Customer teams to understand data needs and prioritize work.
Define team standards for modeling, testing, documentation, monitoring, and on-call.
Contribute hands-on by writing SQL, reviewing pull requests, and building systems while the team is small.

Benefits

Equity in the company.
Fully paid health coverage through Aetna, with 100% of employee premiums covered.
Dental and vision coverage through Guardian.
Carrot Fertility Pro fertility and family-forming support.
12 weeks of paid parental leave.
Unlimited PTO and regular four-day holiday weekends.
401(k) through Vestwell.
Paid relocation support to NYC.
Laptop, monitor, keyboard, and a $200 stipend to personalize the workspace setup.
Catered Friday lunches, team dinners, and unlimited coffee and snacks featuring products from partner brands.