Most of the data moving through our clients' systems was never designed to move cleanly. Your job is to build pipelines that handle that reality, reliable, observable, production-grade, so the analysts, scientists, and dashboards downstream can trust what they're working with.

H3Tech (Healthcare, High-tech, Human) partners with HealthTech companies, insurers, providers, and life sciences organizations to build software that serves clinicians, patients, and administrators. Fully remote, AI-era engineering, with people making every decision that matters.

The Role

You own the data engineering scope on one client engagement. You build and maintain the pipelines, transformations, and data models that power reporting and analytics, working within the delivery cadence, integrating incrementally, and keeping data integrity intact through every change.

What You're Responsible For

Build and maintain data pipelines: ingestion, transformation, and loading across analytics and operational data sources
Write and optimize complex SQL transformations against large-scale datasets, performance and correctness, not just functionality
Design and maintain views, tables, and data models that downstream reporting and application workflows depend on
Lead data integrity and monitoring processes: catch failures before they reach client dashboards or operational systems
Support advanced custom dataset requests, non-standard structures, one-off extracts, ad-hoc analytical builds
Document pipeline architecture and data model decisions clearly enough for QA and delivery teams to verify against
Work within CI/CD gates: ensure pipeline output passes automated quality checks before promotion to production

Qualifications

Required
- Bachelor's degree or above in IT, computer science, or a related field
- 5+ years in data engineering or ETL development with production pipeline ownership
- Comfortable reviewing and steering AI-generated code at volume, catching correctness, security, and quality issues at pace
- Business-level English, data specifications and pipeline documentation are in English
Technical Skills
- Snowflake: warehouses, schemas, access control, query performance tuning, design and implementation level
- SQL: complex transformations, window functions, reconciliation queries at scale, independently, without support
- ETL patterns: solid grounding in transformation logic, data lineage, and pipeline observability
- Scripting: Python for pipeline automation, data processing, and tooling integration
- Orchestration: dbt, Airflow, or equivalent, can configure and maintain, not just execute within
Domain & Compliance
- Working knowledge of data security principles, PII handling, and at least one regulated-industry data environment, healthcare, pharmaceutical, or similar
Strong Advantage
- Experience with marketing automation platform data models: Marketo, Salesforce Marketing Cloud, or equivalent
- Exposure to AI-enabled data tooling: Snowflake Cortex, LLM-assisted pipeline development, or feature store architecture
- Healthcare or pharmaceutical data environments with HIPAA compliance requirements

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