Lead Analytics Engineer

Vero; Boston (MA); Remote; USD 140,000 - 185,000; Full time

Benefits offered by this job

Remote-first environment

Up to $185k total compensation

Own data domain at scale

High-impact role

Collaborative engineering culture

Job summary

Vero is seeking a Lead Analytics Engineer – Data Modeling & Quality to shape trusted data products across the business. The role sits at the intersection of analytics engineering, data modeling, and data quality, building reliable datasets and scalable foundations for healthcare technology solutions.

You will own data models and the semantic layer, drive data quality standards, and partner with Engineering, Analytics, Product, and business stakeholders to align data solutions with outcomes.

Qualifications

• Experience in Analytics Engineering, Data Modeling, or Data Platform Engineering environments.
• Strong understanding of dimensional modeling and transformation design.
• Experience establishing data quality frameworks and governance practices.

Responsibilities

• Lead the design and evolution of scalable data models powering analytics and business outcomes.
• Own transformation and semantic layer converting raw data into trusted datasets.
• Establish and drive data quality standards, validation frameworks, and governance across analytics products.
• Build scalable, maintainable pipelines and transformation logic for long-term reliability.
• Collaborate with Engineering, Analytics, Product, and stakeholders to align data solutions with business outcomes.
• Improve observability, monitoring, testing, and confidence across data products and reporting layers.
• Influence architecture direction to create sustainable foundations for future scale.
• Balance delivery speed with quality and maintainability.

Skills

Analytics engineering

Data modeling

Data platform engineering

Dimensional modeling

Data quality frameworks

SQL

Observability

Stakeholder communication

Tools

dbt

Snowflake

BigQuery

Databricks

Job description

We’re partnered with a fast-scaling healthcare technology company building modern infrastructure that improves healthcare delivery and patient outcomes at scale.

They’re now looking for a Lead Analytics Engineer – Data Modeling & Quality to play a critical role in shaping how trusted data products are built, governed, and delivered across the business.

This position sits at the intersection of analytics engineering, data modeling, transformation architecture, and data quality, helping create reliable datasets and scalable foundations that drive better decisions and operational outcomes across healthcare products and services.

What's on offer

• Total compensation up to $185k
• Remote-first environment with strong flexibility
• Opportunity to own and shape a critical data domain at scale
• High-impact role within a mission-driven healthcare technology business
• Collaborative engineering culture investing in modern data platforms and engineering practices

The Mandate

• Lead the design and evolution of scalable data models powering analytics and business outcomes
• Own the transformation and semantic layer that converts raw operational and clinical data into trusted datasets
• Establish and drive data quality standards, validation frameworks, and governance practices across analytics products
• Build scalable, maintainable pipelines and transformation logic with long-term reliability in mind
• Partner closely with Engineering, Analytics, Product, and business stakeholders to align data solutions with business outcomes
• Improve observability, monitoring, testing, and confidence across data products and reporting layers
• Influence architecture direction and create sustainable foundations for future scale
• Bring structure and clarity to complex data challenges while balancing speed, quality, and maintainability

What We’re Looking For

• Strong experience across Analytics Engineering, Data Modeling, or Data Platform Engineering environments
• Deep understanding of dimensional modeling, transformation design, and building trusted data products
• Experience establishing and operating data quality frameworks and controls
• Strong SQL skills and experience working with modern transformation tooling (dbt or similar)
• Experience building scalable cloud-native data solutions
• Strong understanding of data lifecycle, governance, testing, and observability practices
• Ability to operate across technical and non-technical stakeholder groups
• Pragmatic mindset with the ability to balance delivery timelines and long-term platform quality
• Strong communication skills and the ability to simplify complex data concepts

Bonus

• Experience in healthcare or regulated environments
• Exposure to large-scale operational or clinical datasets
• Experience with modern cloud data platforms (Snowflake, BigQuery, Databricks, etc.)
• Background in platform thinking, reusable frameworks, or self-serve analytics enablement
• Experience introducing data reliability or observability practices at scale