Data & Integration Engineer

Integrated Financial Settlements•Austin, TX

18h•Onsite

About The Position

For over 40 years, Integrated Financial Settlements (IFS) has been transforming lives by helping people achieve financial stability after life-altering events or injuries. Our innovative products and services provide long-term financial security, spendthrift protection, and peace of mind to vulnerable individuals navigating challenging circumstances. We're building the next generation of financial technology to serve our mission more effectively and at greater scale. Our Vision & Values As a collaborative community, our passion is to introduce options that restore stability, encourage hope, and create possibilities for people impacted by injury. We help people navigate change by providing effective financial solutions to support their goals. Our work is guided by four core values: Integrity: Do what is right Innovation: Seek opportunities to learn, improve, and encourage creative thought Collaboration: We are better together. Diversity of experience and thought enriches our work and lives Empathy: Acknowledge others and ask questions. Listen to find out what is important The Opportunity This is a ground-floor opportunity to architect and build the core data and integration backbone of a growing financial services company. You'll design a greenfield enterprise data architecture, connecting internal platforms, third-party systems, banking partners, and external data sources into a unified operating platform. As one of the foundational members of our technology organization, you'll be responsible for creating the architectural patterns, integration frameworks, data models, and AI-ready infrastructure that power the next phase of our growth. You'll transform a business operating across fragmented systems into one powered by trusted data, automated workflows, intelligent decision-making, and secure financial transactions.

Requirements

5+ years of experience in data engineering, integration engineering, platform engineering, solution architecture, or related technical roles
Demonstrated experience building platforms with limited resources and small teams, with a track record of delivering practical solutions that scale as the business grows
Proven experience designing and implementing enterprise data platforms from architecture through production support
Hands-on experience integrating with banking, payment, fintech, or financial services platforms
Strong experience designing APIs, integration services, event-driven architectures, webhooks, and distributed systems
Deep understanding of data modeling, canonical data design, master data management, governance, lineage, and data quality practices
Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, BigQuery, Redshift, or equivalent technologies
Experience building ETL/ELT solutions using tools such as Airflow, Matillion, Fivetran, Azure Data Factory, or equivalent platforms
Strong SQL skills and proficiency in at least one modern programming language such as Python, Java, or C#
Experience implementing secure data transmission, encryption, authentication, authorization, and audit controls
Experience designing solutions for reliability, observability, scalability, compliance, and operational support
Ability to operate across architecture, engineering, and business discussions without requiring specialized teams for every decision

Nice To Haves

Experience building AI-ready data architectures and semantic models
Experience implementing vector databases, embeddings, retrieval-augmented generation (RAG), knowledge graphs, or related AI infrastructure
Experience supporting AI agents, copilots, workflow automation, or agentic architecture
Familiarity with OpenAI, Anthropic, Azure AI, AWS AI services, or other enterprise AI platforms
Experience in integrating structured and unstructured data sources for AI and analytics use cases
Experience with real-time data streaming platforms such as Kafka, Event Hub, Kinesis, or Pub/Sub
Experience in highly regulated industries such as financial services, banking, lending, insurance, or payments
Prior experience in an early-stage, high-growth company where individuals were expected to operate across multiple disciplines

Responsibilities

Build and manage our enterprise data architecture, including canonical data models, data domains, governance standards, lineage, master data strategies, and quality controls
Design and implement a semantic layer that powers analytics, reporting, AI applications, and future agentic workflows
Define enterprise integration architecture, API standards, integration patterns, and reusable connectivity frameworks
Build and manage ETL/ELT pipelines, orchestration frameworks, event-driven processes, observability, monitoring, retry strategies, and operational support
Design secure and compliant data movement across internal, external, and regulated environments
Lead integration efforts with banking and payment systems, including ACH, wire processing, payment networks, custodians, and financial infrastructure providers
Develop integration endpoints and services supporting Salesforce, workflow platforms, customer applications, and external partners
Create data structures and architectures optimized for AI agents, machine learning models, retrieval systems, and intelligent automation
Establish scalable architectural patterns that support future business capabilities while minimizing technical debt
Partner closely with business and technology teams to translate business processes into scalable technical solutions
Evaluate emerging technologies related to AI, data engineering, integration platforms, and cloud architecture