Snowflake Data Engineer - Full time only

• Role: Snowflake Data Engineer
• Location: Remote
• Full time
• Skills: Snowflake, DBT, SQL, Looker, Python, AWS, Commercial Domain, Healthcare Domain.
• Job Description:
• We are currently hiring Data Engineer to help deliver innovative products that allow patients to make life-changing decisions. Our genetic screening and testing help to provide actionable insights to empower people to make critical and timely healthcare decisions by using molecular diagnostic tests for hereditary cancer, urological cancer, depression, and other diseases. We are excited about the future and remain committed to advancing the science of personalized medicine as we develop more products to address unmet medical needs.
• This role on the Data Services Team demands a deep understanding of software development, data engineering principles, and architectural design. They are responsible for architecting and developing data solutions and data engineering pipelines. They work cross-functionally with R&D, technology, and business operations teams to implement data-driven solutions that enhance patient care, drive business insights, and improve operational efficiencies. This role requires a strategic and innovative leader capable of driving impactful solutions across both scientific and business functions.

Responsibilities

• Design, develop, and deploy high-quality software solutions that meet business requirements.
• Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
• Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
• Design and develop data products for reusability and help with data mart standardization
• Domain experience: Commercial experience (Sales operation) is a must; clear understanding of revenue, accounting is a plus.

Software Development:

• Plan, design, analyze, build, maintain, test and enhance
• software systems of both new and existing products/modules.
• infrastructure, architecture, and/or technical strategy across multiple products and teams.
• Data Engineering:
• Collaborate in technical vision and development of a foundation, framework or capability of the team.
• Independently, build architecture for simple to moderate systems. Understand architecture for moderate to complex systems and build in collaboration with other architects.
• Understand end-to-end architecture for complex systems. Guides data architecture to teams across the organization.
• Experience with the tech stack – Snowflake, SQL, dbt and looker is a must. Python is a plus.
• Expert in Cloud technologies – Example: AWS is a plus
• Data Modeling & Looker dashboarding
• Design and implement robust data models to support Commercial Operations reporting and analytics needs.
• Build and maintain commercial, revenue data models that integrate data from CRM, ERP, Marketing, and other operational systems.
• Develop, test, and optimize dbt models to ensure data consistency, quality, and reusability.
• Partner with Data Engineering teams to enhance data pipelines and improve data quality in Snowflake.
• Qualifications
• A Bachelor's degree in a quantitative/technical field (e.g., Computer Science, Engineering)
• 10+ yrs exp industry experience and 2+ yrs Experience with Snowflake (On AWS, GCP, or Azure)
• 5+ years of experience with demonstrated strength in ETL/ELT, data modeling, data warehouse technical architecture, infrastructure components, and reporting/analytic tools.
• 5+ years of experience in scripting languages like Python etc.
• Experience architecting cloud data warehouses is a plus.
• Experience in leading and delivering complex end-to-end projects is a must.
• Experience in Jira, GitHub is a must. Must be familiar with Agile methodologies and be able to participate in scrums, sprint planning, sprint refinements, and retro.
• Experience working with large-scale relational databases, cloud platforms (AWS, Google Cloud), and unstructured data.