Vantive is a vital organ therapy company on a mission to extend lives and expand possibilities for patients and care teams everywhere. For 70 years, our team has driven meaningful innovations in kidney care. As we build on our legacy, we are deepening our commitment to elevating the dialysis experience through digital solutions and advanced services, while looking beyond kidney care and investing in transforming vital organ therapies. Greater flexibility and efficiency in therapy administration for care teams, and longer, fuller lives for patients— that is what Vantive aspires to deliver.

We believe Vantive will not only build our leadership in the kidney care space, it will also offer meaningful work to those who join us. At Vantive, you will become part of a community of people who are focused, courageous and don’t settle for the mediocre. Each of us is driven to help improve patients’ lives worldwide. Join us in advancing our mission to extend lives and expand possibilities.

Key Responsibilities

Data Platform Leadership

·        Provide technical leadership for EDH, AWS S3 ingestion patterns, Snowflake, and enterprise data engineering delivery.

·        Own end-to-end technical design for data ingestion, transformation, orchestration, and curated data product delivery.

·        Establish reusable engineering standards, development patterns, naming conventions, code quality expectations, and operational best practices.

·        Lead technical design reviews and partner with architecture teams to ensure scalable, secure, and maintainable solutions.

·        Drive modernization toward domain-driven data architecture and trusted data products.

Pipeline Development & ETL/ELT Engineering

·        Design, develop, and maintain scalable ETL and ELT pipelines across batch, incremental, CDC, and file-based ingestion patterns.

·        Build and enhance pipelines from source systems into AWS S3 and downstream Snowflake layers.

·        Implement transformation logic, business rules, validations, enrichment, data harmonization, and audit controls.

·        Support common EDH layers and patterns such as collect, translate, curate, and Snowflake consumption layers.

·        Partner with application and BI teams to ensure data pipelines meet business reporting and analytics requirements.

Snowflake Engineering

·        Lead Snowflake development activities including schemas, tables, views, stages, tasks, stored procedures, streams, and secure data access patterns.

·        Optimize Snowflake performance, compute utilization, storage design, query execution, and cost efficiency.

·        Implement role-based access controls, data sharing patterns, security standards, and platform governance expectations.

·        Enable curated datasets and reusable data products for reporting, analytics, AI, and advanced analytics use cases.

Technical Delivery Leadership

·        Lead and mentor data engineers, consultants, and technical delivery teams across design, build, test, deployment, and production support.

·        Review technical designs, code, data models, and deployment packages to ensure quality and adherence to standards.

·        Manage technical dependencies across infrastructure, security, platform, application, and business teams.

·        Drive issue resolution, root-cause analysis, and operational readiness for production releases.

·        Provide hands-on technical guidance when complex pipeline, integration, performance, or data quality issues arise.

Data Quality, Governance & Operations

·        Implement data quality checks, reconciliation controls, observability, lineage, and monitoring across critical data pipelines.

·        Partner with data governance teams to support metadata, cataloging, ownership, access management, and compliance expectations.

·        Ensure pipelines are reliable, supportable, secure, and aligned with enterprise standards for privacy, security, and regulatory needs.

·        Create operational runbooks, support documentation, and transition materials for steady-state operations.

Stakeholder Collaboration

·        Translate business and product requirements into scalable technical solutions and delivery plans.

·        Collaborate with data architects, product owners, business SMEs, BI teams, AI/ML teams, and platform engineering groups.

·        Communicate complex technical topics clearly to both engineeri