Senior Analytics Engineer

Jobgether

United States11h ago

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Key details

Location: United States
Work style: Remote
Level: Senior
Job type: Full-time
Experience: 5–8 yrs
Function: Data & ML
Focus area: Data engineering & Analytics
Posted: 11h ago

Skills

awsazuredata engineeringdata modelingdata qualitydbtgitlucidchartpower bipythonrequirements gatheringsnowflakesqlstakeholder managementtechnical documentationvault

About the role

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Analytics Engineer based in the United States.

This role offers the opportunity to build reliable, scalable data solutions that improve decision-making and operational performance across a rapidly growing healthcare organization. You will lead analytics initiatives from initial problem definition through deployment and ongoing monitoring, translating complex business needs into actionable data products. Working in a highly regulated pharmaceutical environment, you will strengthen data quality, optimize infrastructure, and ensure that business users have access to dependable insights. You will collaborate with stakeholders across the organization while applying modern data engineering and analytics technologies. As a senior individual contributor, you will also mentor colleagues, develop reusable tools, and promote engineering best practices. Your work will directly support more efficient operations and improved access to high-quality medications.

Accountabilities:

You will own analytics delivery across the organization, designing and maintaining data solutions that address business challenges, improve operational reliability, and support strategic decisions.

Lead analytics projects from problem definition and requirements gathering through solution design, deployment, and monitoring.

Identify opportunities for analytics initiatives and develop data-driven business cases outlining expected value, operational benefits, and priorities.

Design scalable, maintainable, and cost-effective data models, pipelines, and reporting solutions to address complex business requirements.

Identify, investigate, and resolve data quality issues while validating analytical outputs and monitoring deployed solutions.

Improve data infrastructure and engineering workflows to reduce recurring issues, increase processing efficiency, and ensure reliable analytics delivery.

Maintain version-controlled code, technical documentation, and structured development practices to support traceability and maintainability in a regulated environment.

Mentor junior team members, share technical knowledge, and promote consistent analytics engineering practices.

Develop reusable tools, libraries, and shared solutions that reduce duplicated work and improve team productivity.

Partner with business stakeholders to clarify requirements, communicate findings through effective data storytelling, and adapt solutions to evolving priorities.

Support responsible AI adoption and identify opportunities to apply emerging technologies to business and analytics processes.

Requirements:

The ideal candidate combines strong analytics engineering expertise with business-oriented problem-solving skills and the ability to deliver reliable solutions in a regulated environment. You should be comfortable working independently, managing ambiguity, and collaborating with both technical and non-technical stakeholders.

At least 5 years of experience in analytics engineering, data engineering, or a related role delivering practical business solutions.

Bachelor’s degree in Computer Science, Engineering, or a related field, or an equivalent combination of education and practical experience.

Strong proficiency in Python, SQL, and data modeling methodologies, including Kimball and Data Vault 2.1.

Hands-on experience with Apache Hop, dbt, Snowflake, AWS, and Azure.

Proficiency in Power BI and DAX, with the ability to translate complex data into clear, actionable insights.

Experience with Git, conceptual data modeling using tools such as Lucidchart, and structured technical problem-solving.

Knowledge of pharmacy operations and the ability to translate business requirements into appropriate data models.

Certified Data Vault 2.0 Practitioner certification.

Strong communication and stakeholder management skills, including the ability to explain technical findings to diverse audiences.

Demonstrated ability to mentor colleagues, share knowledge, and improve engineering practices.

A customer-focused, adaptable, and resourceful approach, with strong accountability and the ability to manage complex challenges.

Experience with responsible AI adoption and the ability to identify opportunities for process and workflow improvements.

Preferred qualifications:

Certified dbt Developer certification.

Microsoft Power BI Data Analyst (PL-300) certification.

Snowflake experience or SnowPro certification.

AWS Data Engineering or AWS Data Analytics certification.

Benefits:

Comprehensive medical, dental, and vision insurance.

Paid time off.

401(k) retirement plan with employer matching.

Wellness perks and employee well-being programs.

Access to IV therapy and compounded medications.

Opportunities for professional development, technical mentorship, and career growth.

Opportunity to contribute to a mission-driven healthcare organization focused on improving medication access and patient care.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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