Senior Data Analytics Engineer [Remote]

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Analytics Engineer in United States.

This role sits at the intersection of data engineering, analytics, and product intelligence, enabling a healthcare technology platform to turn complex operational data into actionable insights. You will play a key role in building and maintaining scalable data pipelines and analytics infrastructure that support critical business and compliance decisions. The environment is highly collaborative, working closely with data scientists, engineers, and product teams to deliver reliable datasets and analytical solutions. You will contribute to the design of robust data models, improve data quality, and ensure seamless access to trusted information across the organization. This position offers strong ownership of analytics engineering initiatives, with the opportunity to influence how data is structured and used at scale. It is ideal for someone who enjoys solving complex data problems and driving impact through clean, reliable, and well-designed data systems.

Accountabilities:

• Design, build, and maintain scalable ETL pipelines that integrate data from multiple sources into centralized data warehouse systems supporting analytics and reporting needs.
• Develop and optimize data models and analytical structures to ensure accurate, efficient, and accessible reporting across business functions.
• Collaborate closely with data scientists and engineers to support the deployment and operationalization of machine learning models and analytical solutions.
• Monitor, validate, and improve data quality by identifying inconsistencies, resolving integrity issues, and implementing robust data testing practices.
• Translate business and stakeholder requirements into technical data solutions that support decision-making and operational efficiency.
• Contribute to the development of data documentation, metadata standards, and governance practices to improve data usability and transparency.
• Evaluate and support the implementation of modern data tools and technologies to enhance the data ecosystem.
• Participate in code reviews and help define best practices for data engineering and analytics development.
• Manage assigned projects independently, ensuring timely delivery of high-quality analytical outputs.
• Continuously identify opportunities to improve data workflows, infrastructure, and analytical performance.

Requirements:

• 4+ years of experience in data engineering, analytics engineering, or a similar data-focused role.
• Strong proficiency in SQL and experience working with relational databases such as PostgreSQL or MySQL.
• Hands-on experience with cloud data platforms such as AWS, Google Cloud, or Azure, and data warehousing solutions like Snowflake, Redshift, or BigQuery.
• Experience with ETL development tools and frameworks such as Apache Airflow and dbt.
• Solid understanding of data modeling concepts and modern data warehouse architecture.
• Proficiency in at least one programming language such as Python or Java.
• Experience with data quality testing frameworks and validation methodologies.
• Strong analytical and problem-solving skills with attention to detail and data accuracy.
• Good communication skills with the ability to collaborate effectively across technical and non-technical teams.
• Experience using Git for version control and collaborative development workflows.

Benefits:

• Competitive compensation package (base salary within an estimated range of $100K–$140K, depending on experience and location)
• Comprehensive medical, dental, and vision insurance options for employees and dependents
• 401(k) plan with company matching and financial planning resources (US-based employees)
• Flexible work arrangements with strong emphasis on work-life balance and remote flexibility
• Generous paid time off, including holidays, birthday leave, and volunteer time off
• Professional development support and learning allowances to encourage continuous growth
• Lifestyle spending account for wellness, fitness, home office setup, and personal needs
• Inclusive and collaborative work culture focused on impact, innovation, and data-driven decision-making

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!

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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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.