Overview

Due to growth, we are adding a Data Analytics Engineer to our team. The Data Analytics Engineer is a key contributor within the Analytics organization, responsible for designing, developing, and maintaining analytics-ready data products and data models that support reporting, analytics, and insight generation. This role reports to the Analytics leadership team and works closely with analytics, business, and data teams. The Analytics Engineer bridges business requirements and analytical outcomes by designing data models, applying business and analytical logic, and creating curated datasets that enable trusted and consistent use of data across reporting and analytics.

Responsibilities

How do I make an impact on my team?

• Design, own, and evolve analytics-ready data models and use-case data products throughout their lifecycle, including data marts, tables, views, and semantic layers that represent business processes and support consistent, performant, and trusted analysis across reporting and analytics use cases.
• Build and maintain analytics-specific transformation, validation, and modeling workflows using authorized enterprise data assets, APIs, relational sources, and structured or semi-structured files to create trusted analytics-ready data products for reporting, analytics, and insight generation.
• Develop and apply analytics engineering standards, modeling patterns, and reference implementations that reduce metric drift, improve consistency, and accelerate adoption of approved analytics technologies.
• Apply software engineering and DataOps practices to automate transformation, testing, orchestration, documentation, version control, and deployment, improving the reliability, observability, and maintainability of analytics solutions.
• Integrate data security, governance, quality, and data management requirements into analytics-ready data products and data models to ensure compliant and responsible use of data across environments.
• Partner with Enterprise Architecture, Data Governance, and enterprise data teams to establish scalable patterns, maintain alignment with enterprise standards, and identify appropriate paths for broader adoption of mature analytical capabilities.
• Optimize analytics-ready data products, data models, and transformation processes for performance, scalability, and cost efficiency within cloud data platforms.
• Partner with Analytics, BI, Data Science, and business teams to translate analytical needs into durable data structures, identify data gaps, and deliver trusted datasets that accelerate insight generation.
• Document reusable patterns and provide technical enablement, consultation, and knowledge transfer to Analytics and BI teams, including supporting the transition of mature capabilities to appropriate operational ownership.
• Support the prototyping and incubation of new analytics products, automations, and AI-assisted capabilities, establishing scalable technical patterns and production-readiness requirements before broader adoption or transition.
• Other duties as assigned.

Qualifications

What our team expects from you?

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Software Engineering, or a related technical field, or equivalent work experience, required.
• 5+ years of professional experience in data analytics, analytics engineering, data engineering, or a related field required.
• Demonstrated experience designing and developing analytics-ready data models, data marts, curated datasets, and data transformation pipelines required.
• Experience working with cloud data platforms and data form sources such as data lakehouses, warehouses, APIs, relational databases, and structured or semi-structured files required.
• Experience using SQL and Python for data transformation and automation and applying software engineering practices such as version control, testing, and documentation required.
• Experience partnering with analytics, BI, and business teams to translate analytical requirements into durable data structures and trusted datasets required.
• Working knowledge of data governance, data quality, and security practices applicable to analytics data assets required.
• Experience with AWS, dbt, Snowflake, Qlik, or similar cloud analytics, data transformation, and BI technologies preferred.
• Experience with AI-assisted development or analytics automation preferred.
• Participate in, adhere to, and support compliance program objectives.
• The ability to consistently interact cooperatively and respectfully with other employees.

What can you expect from Navitus?

• Top of the industry benefits for Health, Dental, and Vision insurance
• 20 days paid time off
• 4 weeks paid parental leave
• 9 paid holidays
• 401K company match of up to 5% - No vesting requirement
• Adoption Assistance Program
• Flexible Spending Account
• Educational Assistance Plan and Professional Membership assistance
• Referral Bonus Program – up to $750!