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Data Engineer

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Remote from
USA
Salary
USD 135k–145k / yr
Employment
Full Time
Experience
Open level
Published
Apply before
28 Nov 2026
Listing views
53
Application actions
5
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AI Summary

The role, at a glance.

Branch is hiring a Data Engineer to build and operate reliable pipelines supporting payments, fraud automation, and client reporting. The role centers on Python, SQL, Airflow, Snowflake, dbt, GCP, API integrations, and production data reliability. The engineer will own pipeline development end to end, including orchestration, testing, observability, incident debugging, and root-cause documentation. This is a mid-level role for someone with at least three years of data engineering and Airflow experience who can work independently in a small, high-trust fintech team.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe role involves production systems tied to financial workflows, requiring strong reliability practices and careful debugging. Its broad ownership across pipelines, APIs, orchestration, and stakeholder requirements raises the technical and operational complexity.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$140,000
US market range (per year)$125k–$165k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary range of $135,000–$145,000 USD. The annual period is inferred from the full-time U.S. professional role and the stated pay magnitude; the estimated U.S. market range for a mid-level Data Engineer with Airflow, Snowflake, dbt, and GCP experience is $125,000–$165,000 annually.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design an Airflow pipeline that ingests data from an external API and loads it into Snowflake?

I would define idempotent tasks for extraction, validation, staging, transformation, and loading, with clear dependencies and retries. I would store credentials in a secrets manager, use incremental checkpoints or watermarks, write raw data to durable storage or staging tables, and use dbt or SQL transformations before publishing curated tables. I would add SLA alerts, data-quality checks, structured logs, and a documented recovery process.

Describe how you would investigate a failed production data pipeline.

I would first assess impact, scope, and freshness requirements through Airflow logs, alerts, and downstream table checks. I would identify whether the failure is due to source availability, authentication, schema drift, infrastructure, transformation logic, or data quality, then apply a safe fix and rerun only the required work. After restoration, I would document the root cause and implement preventive monitoring, tests, or runbook updates.

What practices make a data pipeline reliable and maintainable?

Reliable pipelines are idempotent, observable, tested, and designed with clear ownership. I use version-controlled code, modular shared utilities, schema and data-quality validation, retries with sensible failure handling, alerting, lineage documentation, and incremental processing where appropriate. Consistent naming and reusable patterns also reduce operational burden as the pipeline portfolio grows.

How do you work with stakeholders when requirements for a data product are ambiguous?

I begin by clarifying the business decision or process the data will support, expected consumers, source-of-truth systems, required granularity, refresh cadence, and acceptable data-quality thresholds. I document assumptions and proposed definitions, review a small design or sample output with stakeholders, and surface trade-offs early. This reduces rework and ensures the delivered dataset answers the intended question.

How would you manage schema changes from a third-party API feeding downstream reports?

I would detect schema changes through contract checks and monitoring, preserve raw payloads where possible, and prevent incompatible changes from silently corrupting downstream tables. For additive fields, I would evaluate and roll them out through controlled model updates; for breaking changes, I would coordinate with consumers, version the interface if needed, and communicate timing and impact. I would also add regression tests and update documentation and lineage records.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

About us:

Branch is on a mission to empower workers with financial freedom. We do this by helping companies accelerate payments and providing working Americans with accessible, free financial services. We’re committed to building and delivering more inclusive, transparent, and frictionless financial products.

Our goal of empowerment extends to our own employees, too. Have a great idea? Share it today and it might just get implemented tomorrow. As a member of our team, your voice and creativity matter—and they can directly impact our products, company, and culture.

We not only focus on attracting great talent from across the country, but also on building teams that help that talent thrive. That means valuing a diversity of opinions and working styles, while creating a shared belief in innovation, initiative, and winning together.

Come join our team as we develop new ways to improve the lives of working Americans.

About the role:

Branch helps millions of workers get paid faster and manage their money better. Our team is responsible for the data that drives many critical processes at Branch, including money movement, automated fraud response, and client reporting.

We’re looking for a Data Engineer to join our Data Engineering team. In this role, you’ll work with other engineers and stakeholders to build and maintain the pipelines that power the rest of Branch. You’ll deliver new pipelines and build the underlying components (hooks, utilities, internal libraries) that future pipelines will be built from.

This is a great role for someone with a few years of data engineering experience who’s ready to grow into more end-to-end ownership. Our team is small, high-trust, and values clarity, maintainability, and getting the details right.

What You’ll Do:

  • Build and maintain data pipelines that other teams and customers rely on
  • Integrate with internal and external APIs to send and receive data
  • Orchestrate and automate workflows using Airflow on Kubernetes
  • Implement unit tests, monitoring, and alerting to ensure data reliability
  • Improve the observability and efficiency of existing pipelines
  • Monitor production pipelines, debug issues, and document root causes
  • Work with stakeholders to clarify requirements and validate assumptions
  • Contribute to design discussions and surface functional gaps early

What We’re Looking For:

Required

  • 3+ years of Data Engineering experience
  • 3+ years of Airflow experience
  • Proficiency in Python and SQL
  • Working knowledge of our existing tech stack: Snowflake, Airflow, DBT, GCP
  • BS in Computer Science or related field

Nice to Have

  • Experience in fintech, payments, or a related industry
  • Experience with managing Airflow

Compensation:

The base salary range for this role is $135-145k. The salary range displayed reflects an average base salary range for the position across all the U.S. The base salary offered to an applicant could be higher or lower based on each applicant’s specific skill set, depth of experience, relevant education or training, etc.

Location:

This position is classified as REMOTE within the United States of America.

We are unable to hire candidates located outside of the domestic U.S.

Benefits:

  • Market-leading medical, dental, and vision insurance
  • Stock options
  • Free Premium-Tier Origin Financial Wellness subscription
  • Monthly home-office stipend
  • 401k (TransAmerica)
  • 12-weeks paid parental leave for birthing and non-birthing parents
  • Flexible time off + sick and safe time
  • 11 paid company holidays
  • Branch@Branch Same Day Pay Option

Identity Verification

As part of our application process, you’ll receive a separate email from Greenhouse shortly containing a unique identity verification link. This step, powered by Persona, helps us confirm applicant identities and keep our hiring process secure for everyone.

Upon identity verification, all biometric data is deleted. If you need support completing this application, please reach out to Careers@branchapp.com

Working at Branch

A remote-first company with employees located throughout the U.S., Branch emphasizes transparency, accountability, and trust to create a collaborative environment where our product, engineering, marketing, customer support, customer success, and sales teams can all thrive together. Learn more about what we do in this video!

Our collaborative spirit has helped us become an award-winning FinTech company, with Branch’s innovation and workplace recognized across industries. Branch has been honored by Inc., the Webby Awards, Benzinga FinTech Awards, FinTech Breakthrough Awards, Top Workplaces USA, Great Places to Work, and EY Entrepreneur of the Year, Heartland, among others.

Learn more about our culture, approach, technology, and people here: https://www.branchapp.com/about

Branch is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Must be currently authorized to work in the USA without sponsorship or transfer.

No third-parties, please.

View how Branch collects your personal data here.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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