Role Description This isn't a role where you'll be handed a ticket queue. You'll own meaningful pieces of work, shape how we build, and have a direct hand in what the company becomes over the next few years. - Design and deliver modern data platforms using tools like Snowflake, Microsoft Fabric, Azure, Fivetran, Coalesce, dbt, and Power BI - Lead projects end-to-end - from architecture through to client handover - Champion data governance practices that make platforms trustworthy and scalable - Support clients through the change that comes with adopting new ways of working with data - Help build internal standards and frameworks that shape how the whole team works - Lift capability across the team - by doing good work and being someone others learn from Qualifications - 5+ years of experience in data engineering or modern data platform delivery - Strong SQL and Python, plus hands-on experience with Snowflake, Microsoft Fabric, Fivetran, Coalesce, or dbt - Solid understanding of medallion architecture and dimensional modelling - Familiarity with data governance and metadata tools like Microsoft Purview and Coalesce Catalog - Comfortable using AI tools to accelerate development, whether that's Claude, Snowflake Cortex, or similar - Experience building data pipelines and data products that support AI and ML use cases, including an understanding of what clean, well-structured data looks like for model consumption - A track record of owning projects and delivering results, not just contributing to them - The communication skills to work directly with clients and earn their trust - Previous consulting experience is a plus, but a client-first mindset matters more

Role Description Precision AQ is building a centralized Data Hub to consolidate fragmented data infrastructure, establish enterprise-wide data governance, and enable AI-ready analytics across our life sciences portfolio. This is a foundational initiative, not a maintenance role. We are hiring a Senior Data Engineer to own the development of our Bronze and Silver data layers, the ingestion, transformation, and enrichment pipelines that turn raw healthcare data into governed, reliable, and reusable data assets ready for business use. This role exists because we need engineers who can build at the intersection of healthcare data complexity and modern data engineering best practices. You will work directly with claims, formulary, and other critical data sources, building the pipelines that feed every downstream analytics use case, product, and client deliverable. You will report to the Engineering Director and work closely with the Enterprise Data Architect to translate architecture patterns into production-grade pipelines. This is a hands-on technical role with significant autonomy. If you want to shape how a growing healthcare and life sciences company builds its data foundation, this is the opportunity. Qualifications - Bachelor’s degree in computer science, information systems, engineering, or a related technical field. Advanced degree is a plus but not required. - 5+ years of professional data engineering experience, with at least 3 years working in modern cloud data environments. - 2+ years hands-on experience with Snowflake, including performance tuning, Snowpipe, and Snowflake-specific optimization patterns. - 2+ years working with dbt (Core or Cloud) in production environments, including incremental models, testing, documentation, and package management. - Demonstrated experience with healthcare data, understanding ICD-10, NPI, NDC codes, and the messy realities of claims data quality. - Production experience with orchestration tools, such as Airflow, Dagster, or similar. - Strong SQL skills, with the ability to write efficient, readable, well-structured SQL and debug complex query performance issues. - Python proficiency for data processing, scripting, and pipeline automation. Requirements - Experience with major claims data aggregators (e.g., McKesson, Symphony Health, IQVIA, Komodo). - Familiarity with formulary and payer data. - Experience implementing medallion architecture or similar layered data patterns. - Background in life sciences, pharma services, or healthcare analytics organizations. - Experience with data observability tools. - Exposure to Snowpipe, Matillion, Fivetran, or other managed ingestion solutions. - Familiarity with Git-based workflows, CI/CD for data pipelines, and infrastructure-as-code. Benefits - This is a remote-friendly role with flexibility for EU-based or India-based candidates. - Occasional travel for stakeholder meetings and strategic planning sessions. Who This Role Is For - You want to build foundational data infrastructure in a growing healthcare and life sciences company, not maintain legacy systems. - You’re energized by healthcare data complexity; claims data is messy, and you find that interesting rather than frustrating. - You thrive with autonomy and accountability; you want ownership of outcomes, not just tasks. - You care about craft; clean code, clear documentation, and maintainable systems matter to you. - You want to see the impact of your work; the pipelines you build will power teams across the organization. This role is not for you if - You’re looking for a pure greenfield, no constraints environment; we have an architecture, standards, and patterns. - You prefer highly specialized, narrow scope; this role spans ingestion, transformation, quality, and collaboration. - You want to work in isolation; this is a collaborative team, and you’ll interact regularly within the engineering team and cross-functionally. - You seek a management track; this is a hands-on IC role.

Role Description Precision AQ is building a centralized Data Hub to consolidate fragmented data infrastructure, establish enterprise-wide data governance, and enable AI-ready analytics across our life sciences portfolio. This is a foundational initiative, not a maintenance role. We are hiring a Senior Data Engineer to own the development of our Bronze and Silver data layers, the ingestion, transformation, and enrichment pipelines that turn raw healthcare data into governed, reliable, and reusable data assets ready for business use. This role exists because we need engineers who can build at the intersection of healthcare data complexity and modern data engineering best practices. You will work directly with claims, formulary, and other critical data sources, building the pipelines that feed every downstream analytics use case, product, and client deliverable. You will report to the Engineering Director and work closely with the Enterprise Data Architect to translate architecture patterns into production-grade pipelines. This is a hands-on technical role with significant autonomy. If you want to shape how a growing healthcare and life sciences company builds its data foundation, this is the opportunity. Qualifications - Bachelor’s degree in computer science, information systems, engineering, or a related technical field. Advanced degree is a plus but not required. - 5+ years of professional data engineering experience, with at least 3 years working in modern cloud data environments. - 2+ years hands-on experience with Snowflake, including performance tuning, Snowpipe, and Snowflake-specific optimization patterns. - 2+ years working with dbt (Core or Cloud) in production environments, including incremental models, testing, documentation, and package management. - Demonstrated experience with healthcare data, understanding ICD-10, NPI, NDC codes, and the realities of claims data quality. - Production experience with orchestration tools, such as Airflow, Dagster, or similar. - Strong SQL skills, able to write efficient, readable, well-structured SQL and debug complex query performance issues. - Python proficiency for data processing, scripting, and pipeline automation. Requirements - Experience with major claims data aggregators (e.g., McKesson, Symphony Health, IQVIA, Komodo). - Familiarity with formulary and payer data. - Experience implementing medallion architecture or similar layered data patterns. - Background in life sciences, pharma services, or healthcare analytics organizations. - Experience with data observability tools. - Exposure to Snowpipe, Matillion, Fivetran, or other managed ingestion solutions. - Familiarity with Git-based workflows, CI/CD for data pipelines, and infrastructure-as-code. Benefits - This is a remote-friendly role with flexibility for EU-based or India-based candidates. - Occasional travel for stakeholder meetings and strategic planning sessions. Who This Role Is For - You want to build foundational data infrastructure in a growing healthcare and life sciences company, not maintain legacy systems. - You’re energized by healthcare data complexity; claims data is messy, and you find that interesting rather than frustrating. - You thrive with autonomy and accountability, wanting ownership of outcomes, not just tasks. - You care about craft; clean code, clear documentation, and maintainable systems matter to you. - You want to see the impact of your work; the pipelines you build will power teams across the organization. This role is not for you if - You’re looking for a pure greenfield, no constraints environment; we have an architecture, standards, and patterns. - You prefer highly specialized, narrow scope; this role spans ingestion, transformation, quality, and collaboration. - You want to work in isolation; this is a collaborative team, and you’ll interact regularly within the engineering team and cross-functionally. - You seek a management track; this is a hands-on IC role.

• Design, develop, and maintain robust data processes and solutions to ensure the efficient movement and transformation of data across multiple systems • Develop and maintain data models, databases, and data warehouses to support business intelligence and analytics needs • Collaborate with stakeholders across IT, product, analytics, and business teams to gather requirements and provide data solutions that meet organizational needs • Monitor work against the production schedule, provide progress updates, and report any issues or technical difficulties to lead developers regularly • Implement and manage data governance practices, ensuring data quality, integrity, and compliance with relevant regulations