Cloud Engineer III

Modivcare•Denver, CO

About The Position

Modivcare is looking for an experienced Cloud Engineer III to join our team, responsible for building scalable data pipelines, developing dimensional data models, and creating the transformation layer that powers reporting, self-service analytics, operational applications, and AI initiatives. The ideal candidate is a collaborative and technically skilled data engineering professional with expertise in modern cloud data platforms, data transformation, and enterprise analytics solutions.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field; equivalent combination of education and experience will be considered.
Five (5) or more years of experience in data warehousing, cloud data engineering, or related data platform roles.
Experience designing and developing enterprise cloud data warehouse solutions.
Experience building enterprise ELT/ETL solutions and data integration pipelines.
Experience working with modern cloud data warehouse environments.
Experience supporting reporting, business intelligence, self-service analytics, and enterprise data platforms.
Strong hands-on experience with dbt Core, including development of models, macros, snapshots, tests, documentation, lineage, and reusable transformation frameworks.
Advanced knowledge of SQL, including complex joins, window functions, common table expressions (CTEs), analytical transformations, query tuning, and performance optimization.
Knowledge of dimensional data modeling techniques, including fact tables, dimensions, star schemas, snowflake schemas, and slowly changing dimensions (SCDs).
Proficiency with Amazon Redshift and modern cloud data warehouse technologies.
Knowledge of AWS cloud services, including Redshift, S3, Glue, Lambda, Athena, and Step Functions.
Proficiency in Python for data engineering, automation, and scripting.
Knowledge of Git, CI/CD, and modern software development best practices.
Ability to design, develop, and optimize batch, micro-batch, and near real-time data pipelines.
Ability to build curated data marts and trusted datasets that support reporting, self-service analytics, and downstream applications.
Strong analytical, problem-solving, communication, collaboration, and organizational skills.
Ability to work effectively in Agile environments and collaborate with remote and offshore teams.

Nice To Haves

Experience working in healthcare or another regulated industry is preferred.

Responsibilities

Design, develop, and maintain dbt projects, models, macros, snapshots, tests, and reusable transformation frameworks.
Build and maintain enterprise data transformation pipelines using dbt Core and advanced SQL.
Develop reusable business logic and data models that support reporting, self-service analytics, operational applications, and AI initiatives.
Implement dbt best practices including modular design, testing, documentation, lineage tracking, and source control.
Optimize dbt models and transformation workloads for performance, scalability, and maintainability.
Support CI/CD deployment processes and automated testing for dbt projects.
Collaborate with business and technical teams to translate requirements into scalable and reusable transformation logic.
Develop and maintain cloud data warehouse solutions using AWS services including Redshift, S3, Glue, Athena, Lambda, and Step Functions.
Design and maintain dimensional data models supporting reporting, self-service analytics, and operational data needs.
Build and maintain fact tables, dimensions, star schemas, snowflake schemas, and slowly changing dimensions (SCDs).
Develop curated data marts and trusted datasets for reporting, analytics, and downstream applications.
Partner with business and technical teams to translate requirements into scalable and reusable data models.
Optimize data structures and query performance for large-scale analytical workloads.
Follow established standards and best practices for data modeling, SQL development, and data warehouse design.
Design, build, and maintain batch and near real-time data pipelines supporting enterprise data integration requirements.
Develop ELT/ETL workflows using AWS services, dbt, SQL, and Python.
Integrate data from operational systems, APIs, SaaS applications, healthcare platforms, and third-party data providers.
Support ingestion and transformation of structured, semi-structured, and unstructured data.
Optimize data processing workflows for scalability, reliability, and cost efficiency.
Troubleshoot and resolve data pipeline and data warehouse performance issues.
Partner with application teams, business stakeholders, BI developers, and analytics teams to understand data requirements.
Deliver trusted and well-documented datasets that support reporting and self-service analytics.
Participate in Agile development processes including sprint planning, estimation, code reviews, testing, and release management.
Work effectively with remote and offshore teams to deliver data platform initiatives.

Benefits

Medical, Dental, and Vision insurance
Employer Paid Basic Life Insurance and AD&D
Voluntary Life Insurance (Employee/Spouse/Child)
Health Care and Dependent Care Flexible Spending Accounts
Pre-Tax and Post --Tax Commuter and Parking Benefits
401(k) Retirement Savings Plan with Company Match
Paid Time Off
Paid Parental Leave
Short-Term and Long-Term Disability
Tuition Reimbursement
Employee Discounts (retail, hotel, food, restaurants, car rental and much more!)