Senior Data Engineer

National Association of Insurance Commissioners (NAIC)

. Design, develop, and maintain scalable enterprise data solutions, including data architecture, models, pipelines, structures, and supporting processes within the Enterprise Data Platform (EDP) .

Posted 9/21/2026full-timeRemote • United StatesSenior💰 $107,000 - $123,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable enterprise data solutions, with a strong focus on data architecture, data quality, and governance. Proficient in leading data engineering efforts and mentoring teams while ensuring alignment with business needs and technical standards.

Highest-signal resume keywords

Data ArchitectureSQLETL/ELT DevelopmentData GovernanceCloud-Based Data Technologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingData Pipeline OrchestrationPerformance TuningData Quality TestingData IntegrationData TransformationData Warehouse ConceptsDimensional ModelingRoot Cause AnalysisData Observability

Soft Skills

Technical GuidanceMentoringCollaborationProblem SolvingStakeholder Engagement

Tools & Technologies

Amazon Web Services (AWS)GitTerraformSnowflakeMicrosoft Office Suite/365MacOSNoSQL (MongoDB / DynamoDB)RDBMS (Oracle, PostgreSQL)CI/CD PracticesAgile Delivery Practices

Industry Keywords

Enterprise Data Platform (EDP)Data GovernanceData QualityCloud SecurityData LineageMetadata ManagementData CatalogingData EngineeringData PipelinesData Assets

Tech Stack

Tools & technologies

AWSCloudDynamoDBETLMacOSMongoDBNoSQLOraclePostgresPythonRDBMSSDLCSQLTerraformVault

About the role

Key responsibilities & impact

Design, develop, and maintain scalable enterprise data solutions, including data architecture, models, pipelines, structures, and supporting processes within the Enterprise Data Platform (EDP)
Analyze complex data sources and business requirements with stakeholders to deliver secure, reliable, and efficient data solutions
Develop, optimize, and support data pipelines that ingest, transform, integrate, and deliver trusted data aligned with business needs
Implement data quality, governance, and operational processes to ensure enterprise data assets are accurate, consistent, secure, and well-managed
Provide technical guidance, troubleshooting, and escalation support for teams using or impacting data within the EDP
Perform root cause analysis and sustainable issue resolution
Review and modernize data models, pipelines, and legacy processes to improve scalability, reliability, automation, maintainability, and alignment with enterprise architecture standards
Evaluate emerging technologies, enhance engineering practices, and identify opportunities to expand enterprise data capabilities
Lead complex data engineering efforts, establish and promote engineering standards, mentor team members, and contribute to continuous improvement across the EDP
Partner with data architects, data engineers, data stewards, business owners, project managers, stakeholders, ITG, and business units

Requirements

What you’ll need

Bachelor’s degree in computer science, data analytics, data science, mathematics, statistics, information systems, or another related analytical or technical field and 5 or more years of related data engineering experience; or an equivalent combination of education and work experience
Residency within 100 miles of the Kansas City, Missouri office is required
Applicants must be authorized to work for any employer in the U.S.
Experience designing, developing, and supporting enterprise data platforms, including data ingestion, transformation, modeling, integration, quality, and operational support
Advanced experience with SQL, relational databases, ETL/ELT development, data modeling, and cloud-based data technologies
Experience leading complex technical efforts, making data architecture or design recommendations, and mentoring other technical team members
Experience with the software development life cycle, Agile delivery practices, and SAFe values and methods
Microsoft Office Suite/365
Amazon Web Services (AWS)
Data pipeline orchestration and automation
Extract, Transform and Load (ETL/ELT)
CI/CD and DevOps practices
Git or source control platforms
Infrastructure as Code concepts, such as Terraform
RDBMS (Oracle, PostgreSQL)
NoSQL (MongoDB / DynamoDB)
Snowflake
Python
Structured Query Language (SQL)
MacOS
Data File Formats (JSON, Parquet, XML (likely XBRL in near future))
Data modeling and dimensional modeling
Data warehouse and data Lakehouse concepts
Secrets management concepts, such as Vault or similar tools
Cloud security and IAM concepts
Data governance, lineage, metadata, and cataloging concepts
Performance tuning and query optimization
Data quality testing and data observability
Must not require employment visa sponsorship

Benefits

Comp & perks

Full-time remote position
Positive and flexible environment
No overnight business travel required
Equal Opportunity Employer