Senior Data / Analytics Engineer

Metro Vein Centers is a rapidly growing healthcare practice specializing in state-of-the-art vein treatments. They are seeking a Senior Data / Analytics Engineer to modernize and scale their data architecture across various departments while ensuring the continuity of existing operations.

Responsibilities:

• Help design and implement a scalable modern data architecture within Google BigQuery
• Rebuild and organize fragmented data structures into standardized, maintainable models
• Establish naming conventions, modeling standards, lineage, and governance frameworks
• Help separate and structure sensitive vs non-sensitive data appropriately in a HIPAA-conscious environment
• Partner with leadership to define long-term warehouse and transformation architecture strategy
• Improve scalability and maintainability without disrupting existing business operations
• Own and expand our dbt transformation layer and modeling practices
• Build clean, scalable transformation pipelines and business logic layers
• Create reliable curated datasets for analytics, reporting, operational workflows, and AI initiatives
• Standardize KPI logic and reduce duplicated transformation logic across systems
• Develop testing, QA, and documentation standards for data models and pipelines
• Improve data quality, observability, and reliability across the warehouse
• Build, maintain, and optimize ingestion and transformation pipelines across internal and third-party systems
• Work across platforms including: Google BigQuery, dbt, Fivetran, Portable, Improvado, HubSpot, Tableau, Google Cloud Platform
• Troubleshoot pipeline failures, schema drift, integration issues, and data discrepancies
• Improve monitoring, documentation, and operational stability across the data stack
• Help build structured, reliable, AI-ready datasets and systems
• Partner with Tech & Data leadership on long-term AI infrastructure readiness
• Support future AI-enabled workflows, automation initiatives, and operational tooling
• Contribute to scalable data design practices that support evolving AI use cases across the business
• Partner closely with analysts, marketing, operations, finance, and technology stakeholders
• Support analysts by improving foundational data models and reducing engineering burden on analytics resources
• Collaborate with IT and leadership on governance, access, and long-term platform maturity
• Participate in architectural planning and technical roadmap discussions

Requirements:

• 5-8+ years in analytics engineering, data engineering, or modern data stack environments
• Strong expertise in SQL and warehouse-based data transformation workflows
• Hands-on experience with dbt and modern ETL workflows
• Deep experience working within Google BigQuery or comparable cloud data warehouses
• Proficiency with SFTP-based file transfer workflows, including key-based authentication, scheduled transfers, and error handling
• Experience designing scalable data models and transformation layers
• Experience working with complex operational and business systems data
• Strong understanding of data governance, documentation, testing, and QA practices
• Experience building and maintaining production-grade data pipelines
• Strong systems thinking and architectural judgment
• Ability to balance long-term architecture improvements with short-term operational stability
• Experience with Fivetran
• Experience with Portable
• Experience with Improvado
• Experience with Tableau
• Experience with HubSpot
• Experience with Google Cloud Platform
• Experience in healthcare or HIPAA-conscious environments
• Experience supporting marketing, operational, or revenue-focused analytics ecosystems
• Familiarity with AI-enabled data workflows and AI-ready platform design
• Experience helping mature or rebuild fragmented data environments
• Familiarity with Jira and collaborative technical project management workflows