Cloud Data Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Data Engineer based in the United States.
This role offers the opportunity to build scalable data solutions that support complex healthcare-program challenges.
You will design, develop, test, and optimize data pipelines and warehouse solutions used to turn large datasets into actionable insights.
The position combines hands-on engineering with technical leadership, solution planning, and continuous improvement.
You will collaborate closely with analysts, business stakeholders, and technical teams to translate requirements into reliable data products.
Your work will contribute to efforts addressing fraud, waste, and abuse across healthcare programs.
The environment is highly collaborative and Agile, with a strong emphasis on cloud technologies, automation, data quality, and operational excellence.
This fully remote opportunity is suited to an experienced data engineer who enjoys solving complex problems and taking ownership of high-impact technical work.
Accountabilities:
Design, build, test, debug, and document scalable data solutions for new and existing systems.
Develop and maintain reliable, decoupled data pipelines and data warehouse solutions.
Conduct thorough unit and integration testing to ensure solutions satisfy functional requirements and stakeholder expectations.
Provide senior-level technical guidance for solution architecture, technical planning, and cost-estimation activities.
Lead data engineering initiatives and coordinate development efforts to ensure requirements, milestones, and delivery timelines are met.
Partner with end-user analysts to define, refine, and optimize data warehouse requirements.
Collaborate with business analysts to validate test plans, test cases, and overall solution quality.
Implement CI/CD processes to promote code efficiently across development, testing, and production environments.
Design and maintain job scheduling, orchestration, and workflow automation solutions.
Improve data quality through effective audit, balance, control, and validation practices.
Implement data governance measures, including access controls and role-based security.
Develop cloud-based and event-driven solutions using services such as AWS SQS, Lambda, triggers, and IAM.
Support bulk file ingestion and processing while maintaining reliability, scalability, and data integrity.
Identify opportunities to streamline processes, automate workflows, improve data quality, and increase operational efficiency.
Work within Agile/Scrum teams using collaboration and project-management tools such as Jira and Confluence.
Take ownership of technical issues and customer inquiries, proactively resolving obstacles with minimal guidance.
Collaborate with stakeholders across technical and business functions and contribute ideas that drive continuous improvement.
Bachelor's degree in a relevant field.
8+ years of hands-on experience in data engineering or a related discipline.
Strong programming and scripting skills using technologies such as Python, SQL, shell scripting, and JavaScript.
Experience designing and implementing scalable, decoupled data pipelines.
Strong data warehousing expertise; Snowflake experience is preferred.
Hands-on experience with CI/CD and code promotion across development, test, and production environments.
Experience using Git-based repositories and AWS deployment pipelines, including platforms such as Bitbucket, CodeCommit, or GitHub.
Experience designing job scheduling and data-orchestration workflows.
Strong understanding of data structures, data types, database functions, and data-quality principles.
Experience with bulk file ingestion and processing.
Knowledge of data governance, access controls, and role-based security.
Practical understanding of AWS IAM roles and their integration with AWS-native services.
Experience with AWS data services and event-driven automation, including SQS, Lambda, and triggers.
Experience working with Atlassian tools such as Jira and Confluence.
Experience working within Agile/Scrum environments.
Strong written and verbal communication skills and the ability to collaborate effectively with technical and non-technical stakeholders.
Self-directed, accountable, and proactive approach to solving problems and improving processes.
Ability to learn new technologies quickly and remove technical obstacles with minimal supervision.
Strong commitment to delivering reliable, high-quality results.
Healthcare claims experience is preferred.
Experience using AI-based solutions to identify data or processing defects is desirable.
Familiarity with notebooks such as Jupyter or Snowflake Notebooks is a plus.
Knowledge of data partitioning and clustering techniques for improving performance and controlling cloud costs is desirable.
Experience with data modeling and source-to-target mapping is preferred.
Experience developing serverless architectures and microservices is a plus.
Knowledge of Kimball and Inmon data warehouse methodologies is desirable.
Strong Linux and command-line skills, including Bash, AWS CLI, or Snowflake CLI, are beneficial.
Experience with ETL tools is preferred.
Likely annual salary range of $140,250-$189,750, with actual compensation based on experience, geographic location, and potentially contractual requirements.
Fully remote work arrangement within the United States.
Full-flex work week designed to support work-life balance and personal priorities.
Comprehensive medical plan options, including plans with Health Savings Accounts.
Dental and vision insurance options.
401(k) retirement plan with company matching and pre- and post-tax contribution options.
Paid vacation, sick, and personal leave.
Paid holidays, with employees typically receiving 10 paid holidays annually.
Paid parental, military, bereavement, and jury-duty leave.
Up to 160 hours of paid family leave during a rolling 12-month period for eligible employees.
Short- and long-term disability benefits.
Life insurance and accidental death and dismemberment coverage.
Personal accident, critical illness, and business travel and accident insurance options.
Career-development resources, including AI-powered career tools and internal mobility support.
Opportunities for professional growth and technical learning in data science and engineering.
Less than 10% travel expected.
40-hour standard work week.