Cloud Data Engineer

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

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.

Requirements:

• 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.

Benefits:

• 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.