[Hiring] Lead Data Engineer @Acclinate

Role Description

As Acclinate's Lead Data Engineer, you will design, build, and operate the data infrastructure that powers the company's analytics, CRM, marketing, and machine learning initiatives. This is a hands-on role: you will be equally responsible for long-term architectural strategy and for the day-to-day engineering, pipeline maintenance, and reporting work that keeps Acclinate's data ecosystem running. You'll work across our event-driven architecture, CRM data platform, BI tooling, and production ML systems, partnering closely with the data lead, engineering, marketing, community, and customer success teams.

Key Responsibilities

• Design Event-Driven Data Models and Tables: Architect logical and physical data models, creating necessary data tables and schemas to effectively capture, store, and make accessible vast amounts of data generated by event streams.
• Orchestrate Data Integration for Advanced Analytics: Design integration strategies to combine data from event-driven systems with existing data sources.
• Co-develop Acclinate's Data Strategy: Collaborate with appropriate unit leads and team members to define Acclinate's long-term vision for data.
• Contribute to Data Governance Frameworks: Define data ownership, stewardship, quality standards, metadata management, and data lineage tracking.
• Ensure Data Security and Compliance: Implement data security controls and ensure adherence to relevant data privacy regulations.
• Optimize Data Storage and Performance: Recommend and implement appropriate data storage technologies and indexing strategies.
• Evaluate and Recommend New Technologies: Stay abreast of industry trends and propose new data technologies and tools.
• Oversee Data Integration and ETL/ELT Processes: Build and maintain efficient, reliable data pipelines.
• Own CRM Data (HubSpot): Manage HubSpot property and schema design, maintain the HubSpot-to-BigQuery integration.
• Build and Maintain BI/Analytics Enablement: Build and maintain Metabase dashboards and a shared metrics library.
• Support Production Machine Learning (PPI Model): Own the ongoing data needs of a live production ML model.
• Manage Marketing, Social, and Survey Data Pipelines: Build and maintain daily ingestion pipelines.
• Manage External Data Partnerships: Own tokenized- and identified-data workflows and vendor relationships.
• Build AI Tooling: Develop and maintain Claude data skills for non-technical teams.
• Maintain Data Documentation and Handover Materials: Create and maintain data dictionaries, runbooks, and onboarding materials.
• Apply Engineering Best Practices: Manage all pipeline and transformation code in version control.
• Own Data Quality and Reliability: Define and monitor freshness, completeness, and accuracy checks on critical tables.
• Manage Platform Cost: Monitor and optimize BigQuery and GCP spend.
• Support Compliance Operations: Maintain least-privilege access controls and periodic access reviews on data assets.

Qualifications

• 6+ years building and operating production data pipelines, including at least 2 years owning a data platform end to end.
• Demonstrated ownership of a cloud data warehouse in production. BigQuery preferred; Snowflake, Redshift, or Databricks considered.
• Experience handling regulated health data (HIPAA/PHI) or comparable regulated data.
• Bachelor’s degree in a technical field, or equivalent practical experience.

Requirements

• SQL and BigQuery (primary data platform); Google Cloud Platform (IAM, storage, jobs).
• Python for data preparation, imputation, and analysis notebooks.
• Pipeline and automation tooling (e.g., n8n or equivalent) and scheduled job management.
• HubSpot CRM data model and its BigQuery integration (Operations Hub Enterprise).
• BI tooling, particularly Metabase.
• ML/MLOps exposure: VertexAI and feature pipelines.
• Health-data privacy and compliance awareness (HIPAA/PHI).
• Practical AI tooling experience, including building and validating LLM-based "skills"/agents.

Nice to Haves

• HubSpot Ops Hub data model and its BigQuery sync.
• VertexAI and production ML feature pipelines.
• Building and validating LLM-based agents or “skills”.

Benefits

• Competitive salary commensurate with your experience and qualifications.
• Access to health, dental, and vision insurance plans, with the company covering half of the premium costs.
• Access to 401(k)-retirement plan to help you secure your financial future.
• Enjoy 22 paid holidays throughout the year.
• Receive an educational stipend to support your ongoing professional development.
• A technology allowance to keep you equipped with the tools you need.
• Generous paid time off to recharge and maintain work-life balance.