Health Technology, Pharmacy Benefits Management (PBM), Software Development

Senior Data Engineer

RemoteRemoteFull TimeSeniorPosted 17 days agoVisa sponsorship available

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Required skills

data platform
infrastructure
pipelines
governed data layers
analytics
Snowflake
Apache Airflow
dbt
SQL
data models

Nice to have

pharmacy benefits management
healthcare technology
regulated industry
AWS
Azure
GCP

Role summary

The Senior Data Engineer will own the end-to-end data platform, focusing on designing, building, and maintaining infrastructure, pipelines, and governed data layers for analytics and downstream consumers. This hands-on role emphasizes cloud data platform development, pipeline orchestration, and large-scale data modeling, particularly within Snowflake. Key responsibilities include architecting data flows, ensuring platform reliability and performance, establishing engineering standards (version control, CI/CD, testing), and managing complex workflows with tools like Apache Airflow. The role also involves designing gold-layer data models and governed metrics using dbt, acting as a single source of truth. A significant aspect is building in the AI era, leveraging coding agents and AI-assisted tooling. The ideal candidate has 5+ years of data engineering experience, deep Snowflake expertise, and proficiency in workflow orchestration and dbt.

We are a healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions.

As a leader in SaaS technology for healthcare, we offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem. With our expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace.

Position Summary

The Senior Data Engineer owns the data platform end to end — designing, building, and maintaining the infrastructure, pipelines, and governed data layers that power analytics and downstream consumers across the organization. This is a hands-on engineering role centered on cloud data platform development, pipeline orchestration, and data modeling at scale.

The guiding principle is to build once, consume everywhere — define transformations and metrics a single time, governed and version-controlled in the warehouse, then serve them consistently to every downstream consumer: BI tools, client-facing reporting, and AI systems.

The ideal candidate is comfortable building data platforms and systems from scratch, thrive in a platform development and maintenance environment, and brings strong hands-on experience with Snowflake and workflow orchestration tools such as Apache Airflow and dbt (or equivalent platforms). This role does not own BI visualization — your work spans raw ingestion through the governed gold layer.

Key Responsibilities

Data Platform Development & Maintenance

Design, build, and maintain scalable data pipelines and platform infrastructure on Snowflake.

Architect and implement end-to-end data flows from source ingestion through the silver and gold layers.

Own platform reliability, performance tuning, and ongoing maintenance — treating the data platform as a product.

Build systems from the ground up where needed; evaluate existing systems and refactor for scale, cost efficiency, and maintainability.

Establish engineering standards: version control, CI/CD, testing frameworks, and documentation for all platform components.

Pipeline Orchestration & Workflow Management

Design and maintain orchestration workflows using Apache Airflow (or equivalent) to schedule, monitor, and manage data pipelines.

Ensure pipeline reliability, observability, and failure recovery through alerting, logging, and automated retries.

Coordinate dependencies across upstream sources and downstream consumers with well-defined SLAs.

Gold-Layer Modeling & Metrics

Design, build, and maintain gold-layer data models and a governed metrics layer in Snowflake using dbt — clean, tested, documented, and version-controlled.

Establish metric definitions as the single source of truth: calculated once, reused everywhere, with clear ownership and change management.

Push transformation and calculation logic upstream into the warehouse so the consumption layer stays simple, consistent, and high-trust.

Partner with analytics and BI stakeholders on the boundary between pipelines (data engineering) and consumption (analytics/reporting).

Structure and document data models so they meet the governance and consistency requirements of AI agents and autonomous analytical systems.

AI-Native Development

Build with coding agents and AI-assisted tooling as a primary part of the workflow — accelerating pipeline development, data modeling, documentation, and testing.

Independently set up and manage development environments, repositories, and the tooling needed to work effectively with agentic systems.

Help establish team practices and standards for building data infrastructure in the AI era.

Quality, Governance & Platform Judgment

Champion data quality, consistency, and trust across all platform layers — ensuring data holds up under scrutiny from any downstream consumer.

Contribute to platform architecture decisions; identify opportunities for automation, templating, and process improvement.

Apply sound engineering judgment to evaluate build vs. buy decisions and tooling trade-offs.

Qualifications

Required

5+ years of hands-on experience in data engineering — building pipelines, data models, and platform infrastructure in a data-driven organization.

Snowflake: Proven, hands-on production experience building data models and transformations in Snowflake. Deep familiarity with Snowflake architecture, performance optimization, and cost management.

Workflow Orchestration (must have): Hands-on experience with Apache Airflow or an equivalent DAG-based orchestration platform (e.g., Prefect, Dagster, Mage). Ability to design, deploy, and operate complex pipeline workflows.

dbt: Demonstrated experience using dbt for transformation modeling, testing, and documentation in a production warehouse environment. Equivalent semantic layer tooling experience considered.

Strong SQL proficiency — able to write, optimize, and review complex queries across large datasets.

Experience building data platforms or systems from scratch — not just extending existing infrastructure but designing and standing up new ones.

Comfort with platform development and maintenance as a long-term ownership model — not just project delivery.

Fluency working in the AI era: building with coding agents, setting up development environments, and using AI tooling as a core productivity multiplier.

Familiarity with software engineering practices: version control (Git), CI/CD pipelines, automated testing, and code review.

Strong communication skills — able to translate business requirements into technical data platform decisions.

Preferred

Experience in pharmacy benefits management, healthcare technology, or a related regulated industry.

Experience with cloud infrastructure and data platform tooling (AWS, Azure, or GCP) alongside the data stack.

Familiarity with data governance frameworks, data contracts, or data mesh principles.

Experience with streaming or near-real-time data pipelines (e.g., Kafka, Kinesis, Spark Streaming).

Exposure to semantic/metrics layer tooling (e.g., MetricFlow, Cube, LookML).

Experience building demo environments or client-facing data products.

Salary Range: 145,000 - 165,000

RxSense believes that a diverse workforce is a more talented and productive workforce. As such, we are an Equal Opportunity and Affirmative Action employer. Our recruitment process is free from discriminatory hiring practices and all qualified applicants are considered for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity, ancestry, age, or national origin. Neither will qualified applicants be discriminated against on the basis of disability or protected veteran status. We believe in the strength of the collaboration, creativity and sense of community a diverse workforce brings.

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Senior Data Engineer

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