{"schemaVersion":"jobsearcher.job.v1","id":"7b80e70eaa9f60fc9ceae393","url":"https://jobsearcher.com/jobs/7b80e70eaa9f60fc9ceae393","canonicalUrl":"https://jobsearcher.com/jobs/7b80e70eaa9f60fc9ceae393","title":"Data Engineer","description":"Job Description: Work Location: United States\nWork Mode : Remote\nPay Range :$85K-$140K /Yr Base + Annual Bonus\n\n The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process\n\nFor more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits\n\nJob Overview:\n\nWe are seeking an experienced and visionary Senior Full-Stack Data Engineer to lead the architecture, development, and optimization of a next-generation data platform. This is a critical role for an individual with over 10 years of deep data engineering expertise, capable of driving technical direction, mentoring team members, and delivering high-impact solutions in a fast-paced project environment..\nResponsibilities: Platform Strategy & Leadership\nTechnical Direction: Define and champion the architectural roadmap and best practices for our end-to-end data pipelines, ensuring scalability, reliability, and security across the platform.\nTeam Mentorship & Project Velocity: Act as a primary technical mentor, guiding a team of engineers, conducting code reviews, and aggressively driving the project timeline to ensure rapid delivery of data products.\nStakeholder Collaboration: Partner with Data Scientists, Analysts, and business stakeholders to translate complex requirements into robust, production-ready data solutions.\nCollaboration with Data Scientists and ML Engineers: Data Accessibility, Support for Model Development, Data Quality Assurance\nData Pipeline Development & Management\nIngestion & Transformation: Design, build, and optimize high-volume data ingestion and transformation jobs using tools like dbt Core, AWS Glue, ensuring data quality and integrity.\nWorkflow Orchestration: Develop and maintain sophisticated data pipelines using orchestrators such as Dagster, focusing on modularity and reusability.\nStreaming & Real-time Integration: Implement and manage real-time data flows utilizing Confluent platforms or native AWS streaming services (e.g., Kinesis) for immediate data availability.\nData Security and Privacy: Data Anonymization, Compliance with Regulations\nBe well versed with DataOps and DevOps fundamentals\nAssist and drive the Data Ecosystem Management & Monitoring\nOpen Table Formats & Management: Implement and maintain the Iceberg open table format, utilizing tools for efficient schema evolution and data management.\nCompute Engine Optimization: Optimize query performance and cost efficiency across our primary compute engines: Snowflake, Amazon Redshift, and AWS Athena.\nObservability & Monitoring: Integrate comprehensive monitoring and observability into all pipelines using Splunk to ensure high availability, rapidly identify bottlenecks, and troubleshoot production issues\nQualifications: 10+ Years of hands-on, progressive experience in Data Engineering, Data Architecture, or a closely related Full-Stack Data role\nDeep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata management\nProven track record of building and managing petabyte-scale data infrastructure in a cloud-native environment\nInsurance industry experience preferred but not mandatory\nTools:\nCloud Environment: AWS (S3, IAM, VPC, etc.)\nExperience with Talend, dbt Core, Iceberg, AWS Glue Catalog, Snowflake, Redshift, Athena, Splunk, AWS streaming services, Git\n\nStrong SQL, Pyspark and Python","company":"Ex","rawCompany":"ex","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-10-06T19:55:01.882Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Job Description: Work Location: United States\nWork Mode : Remote\nPay Range :$85K-$140K /Yr Base + Annual Bonus\n\n The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process\n\nFor more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits\n\nJob Overview:\n\nWe are seeking an experienced and visionary Senior Full-Stack Data Engineer to lead the architecture, development, and optimization of a next-generation data platform. This is a critical role for an individual with over 10 years of deep data engineering expertise, capable of driving technical direction, mentoring team members, and delivering high-impact solutions in a fast-paced project environment..\nResponsibilities: Platform Strategy & Leadership\nTechnical Direction: Define and champion the architectural roadmap and best practices for our end-to-end data pipelines, ensuring scalability, reliability, and security across the platform.\nTeam Mentorship & Project Velocity: Act as a primary technical mentor, guiding a team of engineers, conducting code reviews, and aggressively driving the project timeline to ensure rapid delivery of data products.\nStakeholder Collaboration: Partner with Data Scientists, Analysts, and business stakeholders to translate complex requirements into robust, production-ready data solutions.\nCollaboration with Data Scientists and ML Engineers: Data Accessibility, Support for Model Development, Data Quality Assurance\nData Pipeline Development & Management\nIngestion & Transformation: Design, build, and optimize high-volume data ingestion and transformation jobs using tools like dbt Core, AWS Glue, ensuring data quality and integrity.\nWorkflow Orchestration: Develop and maintain sophisticated data pipelines using orchestrators such as Dagster, focusing on modularity and reusability.\nStreaming & Real-time Integration: Implement and manage real-time data flows utilizing Confluent platforms or native AWS streaming services (e.g., Kinesis) for immediate data availability.\nData Security and Privacy: Data Anonymization, Compliance with Regulations\nBe well versed with DataOps and DevOps fundamentals\nAssist and drive the Data Ecosystem Management & Monitoring\nOpen Table Formats & Management: Implement and maintain the Iceberg open table format, utilizing tools for efficient schema evolution and data management.\nCompute Engine Optimization: Optimize query performance and cost efficiency across our primary compute engines: Snowflake, Amazon Redshift, and AWS Athena.\nObservability & Monitoring: Integrate comprehensive monitoring and observability into all pipelines using Splunk to ensure high availability, rapidly identify bottlenecks, and troubleshoot production issues\nQualifications: 10+ Years of hands-on, progressive experience in Data Engineering, Data Architecture, or a closely related Full-Stack Data role\nDeep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata management\nProven track record of building and managing petabyte-scale data infrastructure in a cloud-native environment\nInsurance industry experience preferred but not mandatory\nTools:\nCloud Environment: AWS (S3, IAM, VPC, etc.)\nExperience with Talend, dbt Core, Iceberg, AWS Glue Catalog, Snowflake, Redshift, Athena, Splunk, AWS streaming services, Git\n\nStrong SQL, Pyspark and Python","datePosted":"2026-10-06T19:55:01.882Z","dateModified":"2026-10-06T19:55:01.882Z","hiringOrganization":{"@type":"Organization","name":"Ex","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"7b80e70eaa9f60fc9ceae393"},"url":"https://jobsearcher.com/jobs/7b80e70eaa9f60fc9ceae393"}}