Senior Data Analytics Engineer

Role Overview

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. The environment is highly collaborative, working closely with data scientists, engineers, and product teams to deliver reliable datasets and analytical solutions.

What You Will Do

Design, build, and maintain scalable ETL pipelines, develop and optimize data models, collaborate with data scientists and engineers, monitor and improve data quality, and translate business requirements into technical data solutions.

Why It Might Be a Fit

Ideal for someone who enjoys solving complex data problems and driving impact through clean, reliable, and well-designed data systems. Strong ownership of analytics engineering initiatives, with the opportunity to influence how data is structured and used at scale.

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

Tagged as: Data Analysis