Data Engineering Manager

Confido Health, Inc.; New York (NY); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity

Health coverage (Aetna)

Dental and vision coverage

Fertility and family-forming support

Parental leave

Unlimited PTO

401(k)

Relocation assistance to NYC

Workspace stipend

Team lunches and outings

Job summary

Confido Health, Inc. is seeking a Data Engineering Manager in NYC to lead our data team responsible for customer-facing reports, internal dashboards, and day-to-day decision-making.

You will start by guiding the Senior Analytics Engineer, handle hiring as the team grows, and write substantial code early on. You will shape warehouse design, pipelines, and tooling, while collaborating with Engineering, Product, Ops, and Customer teams to define data needs and metrics.

Qualifications

• 7+ years in data or analytics engineering, with at least 2 years managing engineers.
• Built a data warehouse from an early or messy state and kept it running.
• Strong SQL and data modeling skills; built and maintained ETL/ELT pipelines in production.
• Experience with Snowflake, dbt, Airflow, Dagster, or similar tools.
• Has hired engineers and helped them grow in their roles.
• Able to translate vague data requests into concrete plans.
• Able to split time between management and hands-on work.

Responsibilities

• Manage and develop the data team, starting with the Senior Analytics Engineer.
• Set priorities for the team and communicate plans to the company.
• Make big technical decisions on warehouse design, pipelines, orchestration, and tooling.
• Hire data engineers as we grow; write job descriptions, conduct interviews, onboard new hires.
• Set standards for modeling, testing, docs, monitoring, and on-call.
• Collaborate with Engineering, Product, Ops, and Customer teams to define metrics and data needs.
• Be accountable when numbers are wrong or pipelines break, and implement fixes to prevent recurrences.
• Write SQL, build models, and review PRs, especially early on.

Skills

People management

SQL

Data modeling

ETL/ELT pipelines

Data warehousing

Prioritization

Communication

Tools

Snowflake

dbt

Airflow

Dagster

Job description

The brands on your kitchen shelf are run by people doing extraordinary work that nobody sees. We're building the platform they run on, and a brand they'll be proud to be part of. Confido is the AI operating system that runs cash application, deductions, trade and planning in one place for CPG brands. That means Finance, Sales, and Ops finally work on the same number. We’re trusted by 250+ brands managing $30B+ in revenue, including Daisy, OLIPOP, Simple Mills, Idahoan, and more. We've achieved best-in-class growth and recently raised a $55M Series B led by Insight Partners to accelerate our momentum.

If you want your work on shelves everywhere — and outsized ownership while you build — we'd love to meet you.

THE ROLE

Data at Confido feeds customer-facing reports, internal dashboards, and a lot of day-to-day decisions. Right now it lives in too many places and is owned by too many people. We're hiring a Data Engineering Manager to fix that and to build the team that keeps it fixed.

You’ll manage our Senior Analytics Engineer to start, and you’ll hire as the team grows. For the first stretch you’ll write a good amount of code yourself. Later, more of your time will go to hiring, planning, and working with other teams.

What You’ll Do

• Manage and develop the data team, starting with our Senior Analytics Engineer.

• Decide what the team works on and in what order, and explain those calls to the rest of the company.

• Make the big technical decisions on warehouse design, pipelines, orchestration, and tooling.

• Hire data engineers as we grow. You’ll write the job descriptions, run the interviews, and onboard new hires.

• Set standards for modeling, testing, docs, monitoring, and on-call.

• Work with Engineering, Product, Ops, and Customer teams to agree on metric definitions and figure out what data they actually need.

• Be accountable when numbers are wrong or pipelines break, and put fixes in place so the same problems don't come back.

• Write SQL, build models, and review PRs, especially early on.

What We’re Looking For

• 7+ years in data or analytics engineering, with at least 2 years managing engineers.

• You’ve built a data warehouse from an early or messy state before, and you’ve kept it running afterward.

• Strong SQL and data modeling skills. You’ve built and maintained ETL/ELT pipelines in production.

• Experience with Snowflake, dbt, Airflow, Dagster, or similar tools.

• You’ve hired engineers and helped them get better at their jobs.

• You can take a vague request like "we need better reporting," figure out what's really needed, and turn it into a plan.

• You’re happy splitting your time between managing and building.

Success in This Role

A year in, people across Confido trust the data and know where to find it. There's one set of core models the whole company uses, pipelines break less often, and when they do break, someone notices before a customer does. The team is bigger than one person, and it has clear standards that new hires can pick up quickly.

Perks + Benefits

• Equity — own a meaningful piece of the company you’re helping build

• Fully paid health coverage through Aetna — we cover 100% of employee premiums

• Top-tier dental and vision coverage through Guardian

• Carrot Fertility Pro — comprehensive fertility and family-forming support

• 12 weeks of paid parental leave

• Unlimited PTO — plus regular 4-day holiday weekends we actually take

• 401(k) through Vestwell

• Paid relocation support — we’ll help you make the move to NYC

• Fully equipped workspace from day one — laptop, monitor, keyboard, and a $200 stipend to personalize your setup

• Team perks — catered Friday lunches, team dinners, and unlimited coffee + snacks featuring products from the brands we work with

Confido provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.