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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Engineer, Payment Operations - **Company:** Zelis Healthcare - **Location:** St. Louis, MO, United States - **Experience:** Expert - **Salary:** $127,000.0 - $160,550.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Batch Processing, Big Data, Cloud Computing, Cluster Analysis, Information Systems, Data Architecture, Information Engineering, Data Governance, Database Queries, Database Schema, Job Scheduling, Python (Programming Language), Operational Databases, Performance Tuning, Reverse Engineering, SQL Stored Procedures, SQL Databases, Data Streaming, Snowflake, Backend, Information Technology, Looker Analytics, Data Pipelines - **Published:** August 21, 2026 - **Apply:** https://zelis.wd1.myworkdayjobs.com/ZelisCareers/job/US-MO-St-Louis-Corp/Sr-Data-Engineer--Payment-Operations_JR111602 ## About the Role * 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. ## Description The Senior Data Engineer leads the engineering workstreams that underpin the Payment Operations monitoring transformation program at Zelis. This role designs, builds, and maintains Snowflake data pipelines; activates payment monitoring scenarios; and delivers the KPI infrastructure used for executive reporting across multiple platforms. As the primary Snowflake subject matter expert for Payment Operations, the role also strengthens data literacy, documents the data architecture, and provides technical guidance that enables the broader operations organization to use data more independently., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Software Developer Salary in Switzerland [2023]](https://www.wearedevelopers.com/magazine/215-software-developer-salary-in-switzerland-2023)