Senior Software Engineer, Integrations & Data

Wilks Brothers•Fort Worth, TX

5d•Onsite

About The Position

Equify Financial is hiring a high-ownership backend engineer to build and operate integrations between its core vendor platforms and develop the data pipelines that bring information into its Databricks lakehouse. The role connects systems used for loan origination, servicing, CRM, documents, accounting, and credit data, supporting business workflows as well as reporting, reconciliation, and audit needs. The engineer will own production integrations and data ingestion, change data capture, and transformation layers. Reliability is central to the work: integrations and pipelines should include appropriate idempotency, error handling, testing, monitoring, recovery, and reconciliation. The role also uses modern AI coding tools to accelerate design, implementation, testing, and documentation. The position works closely with Equify’s technology team, risk and analytics team, business users, and platform vendors. It reports directly to the Director of Business Systems and is based in Equify’s Fort Worth, Texas office. It is an in-office role and is not eligible for remote or hybrid work.

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 backend development skills in Python and 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, including 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, along with the engineering fundamentals to direct these tools and validate their output.
Able to perform essential functions including prolonged desk and computer work, lifting up to 15 pounds at times, positioning to install equipment, moving throughout the building to access files, following written and oral instructions, completing tasks with frequent interruptions, using discretion and independent judgment, and speaking clearly on the phone and with coworkers.

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.
Precision, ownership, pragmatism, and a collaborative approach to technical decision-making.

Responsibilities

Design, build, and operate backend integrations between core platforms, including loan origination, loan servicing, Salesforce, Microsoft Dynamics 365 Business Central, document, and credit-data systems.
Build APIs, services, and middleware connecting vendor systems using REST APIs, webhooks, and message queues as appropriate.
Engineer production 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 integration contracts and behavior.
Own data ingestion from connected systems into the Databricks lakehouse, including change data capture and incremental loads.
Design and maintain transformation layers used for reporting, analytics, and reconciliation, including correct handling of history, deletes, and late-arriving changes.
Define and enforce schema contracts with upstream systems so format changes are caught 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.