Senior Software Engineer, Integrations & Data

CARBO•Fort Worth, TX

1d•Onsite

About The Position

Equify Financial is hiring a backend engineer to build and operate integrations between its core vendor platforms and own the data pipelines that bring information into its Databricks lakehouse. The position connects systems used for loan origination, servicing, CRM, documents, accounting, and credit data, supporting timely transaction handoffs as well as reporting, reconciliation, and audit needs. The engineer will develop API-based services and middleware, build ingestion and transformation layers, and ensure integrations and pipelines operate reliably in production. The role emphasizes accuracy, idempotency, error handling, testing, monitoring, schema contracts, and reconciliation. The engineer will collaborate with the technology, risk, and analytics teams and external platform vendors, and will use modern AI coding tools to accelerate design, implementation, testing, and documentation. The position reports directly to the Director of Business Systems. This is an in-office position at Equify Financial's Fort Worth, Texas offices; remote and hybrid work are not available. Working conditions include prolonged periods sitting at a desk and using a computer, occasional lifting of up to 15 pounds, positioning to install equipment including under desks, and moving through the building to access files. The role also requires following written and oral instructions, completing tasks amid frequent interruptions, using discretion and independent judgment, and speaking clearly by phone and with coworkers.

Requirements

High school diploma or equivalent.
At least 5 years of professional backend or data engineering experience, including ownership of production integrations or pipelines.
Strong Python backend development skills plus experience with at least one of C#/.NET or TypeScript/Node.js, including building and operating API-based services.
Hands-on experience designing, building, and consuming REST APIs, including OAuth and token-based authentication, pagination, rate limits, and versioning.
Experience integrating third-party enterprise or SaaS platforms and applying reliability patterns such as idempotency, retries, dead-letter handling, and reconciliation.
Experience with event-driven and asynchronous integration patterns, such as webhooks, message queues, or serverless functions.
Hands-on experience with Databricks or a comparable lakehouse platform, including Spark and Delta Lake.
Expert SQL skills and experience with change data capture and incremental processing.
Hands-on experience with Microsoft Azure and the broader Microsoft ecosystem.
Experience applying CI/CD, version control, and automated testing to services and data pipelines.
Ability to independently drive work from requirements through production.
Ability to work through ambiguity and make sound technical tradeoffs without heavy process or structure.
Ability to work directly with business users, analysts, and vendors, ask relevant questions, and explain technical issues in business terms.
Fluency with modern AI-assisted development, together with the engineering fundamentals to guide the tools and validate their output.

Nice To Haves

Experience with Azure Functions or Azure Service Bus.
Experience with Salesforce or Dynamics 365 Business Central APIs and data models.
Experience with Databricks Lakeflow or Delta Live Tables.
Background in equipment finance, lending, or leasing, including loan origination and servicing systems.

Responsibilities

Design, build, and operate backend integrations between Equify's core platforms, including loan origination, loan servicing, Salesforce, Microsoft Dynamics 365 Business Central, document, and credit-data systems.
Build APIs, services, and middleware between vendor systems using REST APIs, webhooks, and message queues as appropriate.
Engineer production-ready integrations with authentication, retries, idempotency, error handling, logging, and replay capabilities.
Work with platform vendors on API capabilities, field mappings, and integration testing, and document each integration's contract and behavior.
Own data ingestion from core systems into the Databricks lakehouse, including change data capture and incremental loads.
Design and maintain transformation layers for reporting, analytics, and reconciliation, correctly handling history, deletes, and late-arriving changes.
Define and enforce schema contracts with upstream systems so format changes are detected at system boundaries.
Establish shared customer, contract, and asset keys to match records across systems and in the lakehouse.
Build monitoring, alerting, and reconciliation checks across integrations and pipelines to surface failures and mismatches.
Replace manual re-keying and recurring manual data preparation with maintained, documented automation.
Build the integration and data foundation for planned customer-facing platforms.
Use modern AI coding tools to accelerate design, implementation, testing, and documentation.