
Kanbrick
Data engineer
Lead the creation of production-grade infrastructure and develop reliable technology for reporting. Build and maintain data pipelines to ensure clean data flow into the warehouse.

Abacus Insights
·yesterdayAbacus Insights
·yesterdayLocation
remote, United States
Salary
$60k/yr
Commitment
Full Time
Level
Junior (<2 years)
Abacus Insights is transforming how data and AI work for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence.
As the AI and Data Platform for Payer Intelligence, we help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions—so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we're tackling big challenges in an industry that's ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows—and it's why we are leading the way.
Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable—those excited to leverage emerging technologies to enhance how we work—while keeping human insight, connection, and our clients at the center of every decision.
Ready to make an impact? Join us and let's build the future together.
Our Data Engineering team is looking for an Associate Data Engineer. In this role, you will partner with clients, implementation teams, and internal stakeholders to help deliver high-quality data extracts and distribution solutions from Abacus’s core data management platform, which is built on scalable, flexible, and resilient cloud architectures.
This is an early-career opportunity designed for recent graduates who are excited to build a foundation in data engineering, healthcare data, and client-facing delivery. As a trusted partner to the team, you will support client adoption of Abacus’s data management offerings while developing hands-on experience in data analysis, mapping, SQL, data quality, and cloud-based data services.
Compensation for this role is $30/hour or $62,400 per annum.
As a mission-led technology company helping to drive better healthcare outcomes, Abacus Insights believes that the best innovation and value we can bring to our customers comes from diverse ideas, thoughts, experiences, and perspectives. Therefore, we dedicate resources to building diverse teams and providing equal employment opportunities to all applicants. Abacus prohibits discrimination and harassment regarding 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.
At the heart of who we are is a commitment to continuously and intentionally building an inclusive culture—one that empowers every team member across the globe to do their best work and bring their authentic selves. We carry that same commitment into our hiring process, aiming to create an interview experience where you feel comfortable and confident showcasing your strengths. If there’s anything we can do to support that—big or small—please let us know.
We use AI-powered tools throughout our recruitment process. This includes Greenhouse's Real Talent Matching Technology, which helps prioritize applications based on job-related criteria, as well as additional AI tools used to support sourcing, interview preparation, and other recruiting tasks. We do not remove the human element—our recruiters and hiring teams review all applications and make all decisions related to candidate progression and hiring, regardless of which tools are used to support that process.
To protect the integrity of our hiring process, all interviews are conducted by live video with your camera on. Virtual or blurred backgrounds and headsets are not permitted absent an approved accommodation, and you should be in a well-lit, private space where your face and surroundings are clearly visible. Candidates who advance may also be asked to complete identity and location verification, which may include verifying your identity, work history, and confirming that you are located where your application states. Applications containing knowingly false or materially misrepresented information, including identity, location, or credentials, may be disqualified, and any offer may be rescinded if a material misrepresentation is discovered at any point in the process.
If you need an accommodation for any part of the interview process, please let your recruiter know in advance.
By applying, you acknowledge that we will collect and process your personal information for recruiting purposes in accordance with applicable data protection laws, including for the verification steps described above. Please review our Applicant Privacy Notice for more information, including your rights.

Kanbrick
Lead the creation of production-grade infrastructure and develop reliable technology for reporting. Build and maintain data pipelines to ensure clean data flow into the warehouse.

Grainger Businesses
Design and implement scalable data processing systems and pipelines using Kubernetes, Databricks, and Snowflake. Define platform patterns for AI-ready data products and support Snowflake AI initiatives. Educate teams on new data patterns and tools while mentoring junior members.

S R INTERNATIONAL INC
Design and maintain data pipelines, integrate and transform datasets, and improve data quality. Develop analytics solutions to support program delivery and decision-making. Collaborate with cross-functional teams and automate processes to enhance operational efficiency.
Octans Llc
Design, build, and maintain scalable data pipelines and ETL/ELT workflows. Develop and manage data warehouses, data lakes, and relational/non-relational databases. Monitor and optimize data infrastructure for performance, reliability, and scalability.

beehiiv
Build and maintain Clickhouse Data Models and Aggregations for analytics. Collaborate with Product Engineering to design event streaming applications. Automate deployments of schemas, manage database migrations, and enhance the Kafka Streaming Ecosystem.

Huzzle
Design, build, and maintain scalable ETL and ELT data pipelines. Develop and optimize data architectures, databases, and data warehouses. Integrate data from various sources and maintain data quality and security.

Aston Carter
Design, develop, and enhance data processes for collecting, transforming, organizing, and delivering large volumes of data. Use SQL for complex data transformations and build VertiPaq semantic models.