Sr. Data Engineer, Payment Operations

Zelis is modernizing the healthcare financial experience across payers, providers, and healthcare consumers. We serve more than 750 payers, including the top five national health plans, regional health plans, TPAs and millions of healthcare providers and consumers across our platform of solutions. Zelis sees across the system to identify, optimize, and solve problems holistically with technology built by healthcare experts – driving real, measurable results for clients.

At Zelis, AI is woven into the fabric of how we work. Every associate is expected - and empowered - to partner with AI to challenge the status quo, accelerate innovation, and amplify their impact. This is a place for builders with a growth mindset who act with agility, embrace change, and use modern technology to shape smarter solutions, exceptional experiences, and the future of our industry for our clients, customers, and our culture.

You bring a unique blend of personality and professional expertise to your work, inspiring others with your passion and dedication. Your career is a testament to your diverse experiences, community involvement, and the valuable lessons you've learned along the way. You are more than just your resume; you are a reflection of your achievements, the knowledge you've gained, and the personal interests that shape who you are.

Key Responsibilities

Payment Monitoring Engineering: Design, build, deploy, and maintain Snowflake tables and pipelines that support payment monitoring. Develop stored procedures, status-specific delay thresholds, business-day-aware timing windows, and root cause diagnostic tagging. Maintain the combined platform monitoring table that supports top-down alerting across the full payment lifecycle.

Monitoring Scenario Activation: Execute activation of inactive monitoring scenarios in sequenced sprints with prioritization based on cost, risk, and revenue exposure.

KPI Infrastructure: Design and maintain the Payment Lifecycle KPI calculation pipeline, including query logic, data joins across tables and source payment records, and automated refresh cadence — with slicing by any required dimension such as platform, payer, and payment modality.

Data Quality Management: Establish and maintain data quality controls within payment pipelines, including forward-fill logic, export grouping, source system column validation, and definitional consistency checks between payment-related data sources.

Technical Leadership and Enablement: Serve as the primary Snowflake subject matter expert for Payment Operations. Lead working sessions with onshore and offshore partners to build practical SQL and Snowflake proficiency, review technical approaches, and promote maintainable engineering practices.

Architecture and Documentation: Document the Payment Operations data architecture, including platform schemas, table structures, data flows, dependencies, stored procedures, operational runbooks, and monitoring logic to ensure knowledge is accurate, transferable, and sustainable.

Cross-Functional Partnership: Translate business monitoring needs into scalable technical solutions and communicate technical findings, risks, tradeoffs, and recommendations in clear language to operations leaders and non-technical stakeholders.

Required Qualifications

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field; or equivalent professional experience in lieu of degree.

7 years of experience in data engineering, with at least 3 years in production Snowflake environments.

Expert SQL proficiency, including recursive common table expressions, stored procedures, and performance tuning on large-scale datasets.

Hands-on experience with Snowflake-native patterns, including Snowpipe, streams and tasks, clustering, and virtual warehouse configuration.

Demonstrated ability to absorb an unfamiliar data architecture quickly — reading existing schemas, reverse-engineering legacy stored procedures, and mapping undocumented data flows.

Experience building and supporting production data pipelines, monitoring workflows, automated batch processes, and data quality controls.

Experience with enterprise job scheduling tools such as Automic, Airflow, or dbt Cloud for managing production batch workloads.

Preferred Skills

Experience working as an embedded data engineer within a business operations team, with the ability to translate technical work into plain language for non-technical colleagues.

Comfort working with AI tools and applying them to accelerate data engineering workflows, analysis, and documentation.

Experience in healthcare payment processing, including ACH, EDI 835 delivery, virtual card (VCC or VRA), or provider payment disbursement workflows.

Familiarity with SIGMA or equivalent cloud-native BI platforms (Looker, Hex, or similar) connected to a Snowflake backend.

Exposure to HIPAA-compliant data handling practices and healthcare data governance frameworks.

Experience conducting peer reviews of Python, SQL or pipeline code in a cross-functional setting.

Snowflake SnowPro Core or Advanced certification.

Please note at this time we are unable to proceed with candidates who require visa sponsorship now or in the future.

The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified. All personnel may be required to perform duties outside of their normal responsibilities, duties, and skills from time to time.