{"schemaVersion":"jobsearcher.job.v1","id":"79878f7369dbdd4336e8a69e","url":"https://jobsearcher.com/jobs/79878f7369dbdd4336e8a69e","canonicalUrl":"https://jobsearcher.com/jobs/79878f7369dbdd4336e8a69e","title":"Data Engineer","description":"Data EngineerLocation: Remote (USA)Employment Type: ContractWork Authorization: US Citizen (USC) or Green Card (GC) Holders OnlyExperience Level: 3–5 YearsRole SummaryWe are seeking a detail-oriented and skilled Data Engineer with 3–5 years of hands-on experience to design, build, and maintain scalable data pipelines and cloud-based analytics solutions. In this role, you will play a crucial part in architecting seamless ETL/ELT workflows using Snowflake, Azure Data Factory, and Azure Databricks. The ideal candidate brings strong technical expertise in data modeling, pipeline orchestration, and query optimization, with a strict commitment to data quality, security, and system reliability.Key ResponsibilitiesPipeline Engineering: Design, build, test, deploy, and maintain batch and near-real-time ETL/ELT data pipelines for structured and semi-structured datasets.Orchestration & Workflow Management: Build and orchestrate data ingestion and transformation workflows using Azure Data Factory and Azure Databricks.Data Warehousing & Modeling: Develop scalable data models, transformations, stored procedures, and performance-optimized workloads within Snowflake.Data Processing: Utilize PySpark, Python, and SQL to cleanse, integrate, validate, and transform data across various enterprise and cloud data sources.Reliability & Monitoring: Implement robust logging, monitoring, alerting, retry, and error-handling mechanisms to ensure high pipeline availability and uptime.Governance & Security: Apply data-quality frameworks, reconciliation controls, lineage tracking, documentation standards, and strict role-based access security.Cross-Functional Collaboration: Partner with solution architects, data analysts, application teams, and business stakeholders to translate complex requirements into scalable data solutions.DevOps & Maintenance: Participate in code reviews, CI/CD deployment pipelines, production support, root-cause troubleshooting, and continuous query/cost optimization.Required QualificationsEducation: Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.Experience: 3–5 years of hands-on experience in data engineering, data integration, or cloud data platform development.Core ETL/ELT: Strong background in designing end-to-end data pipelines and deep familiarity with dimensional modeling and data warehousing concepts.Snowflake Proficiency: Solid hands-on experience with Snowflake, including data loading, complex transformations, query tuning, and virtual warehouse optimization.Azure Data Factory (ADF): Practical experience setting up linked services, datasets, pipelines, triggers, and orchestration.Azure Databricks & PySpark: Hands-on experience with Azure Databricks, Apache Spark/PySpark, notebook workflows, cluster management, and Delta Lake concepts.Programming & Querying: Advanced proficiency in SQL and solid working experience with Python for integrating data from relational databases, flat files, REST APIs, and cloud storage.Version Control & Methodology: Familiarity with Git-based version control, CI/CD practices, Agile/Scrum delivery, and cloud security best practices.Soft Skills: Excellent problem-solving, analytical, troubleshooting, written documentation, and verbal communication skills.Preferred Skills & CertificationsTechnologies: Azure Data Lake Storage Gen2 (ADLS Gen2), Delta Lake, Snowpipe, and dbt (data build tool).Tools: Azure DevOps, Git, and REST API integration.Concepts: Data governance, data lineage, and metadata management.Certifications: Active certifications in Microsoft Azure (e.g., Azure Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a strong plus.How to ApplyIf you meet the requirements above and are looking to join a dynamic, data-driven environment, please submit your updated resume outlining your relevant experience.","company":"Global Applications Solution","rawCompany":"global applications solution","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-10-20T10:41:14.410Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"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":"Data EngineerLocation: Remote (USA)Employment Type: ContractWork Authorization: US Citizen (USC) or Green Card (GC) Holders OnlyExperience Level: 3–5 YearsRole SummaryWe are seeking a detail-oriented and skilled Data Engineer with 3–5 years of hands-on experience to design, build, and maintain scalable data pipelines and cloud-based analytics solutions. In this role, you will play a crucial part in architecting seamless ETL/ELT workflows using Snowflake, Azure Data Factory, and Azure Databricks. The ideal candidate brings strong technical expertise in data modeling, pipeline orchestration, and query optimization, with a strict commitment to data quality, security, and system reliability.Key ResponsibilitiesPipeline Engineering: Design, build, test, deploy, and maintain batch and near-real-time ETL/ELT data pipelines for structured and semi-structured datasets.Orchestration & Workflow Management: Build and orchestrate data ingestion and transformation workflows using Azure Data Factory and Azure Databricks.Data Warehousing & Modeling: Develop scalable data models, transformations, stored procedures, and performance-optimized workloads within Snowflake.Data Processing: Utilize PySpark, Python, and SQL to cleanse, integrate, validate, and transform data across various enterprise and cloud data sources.Reliability & Monitoring: Implement robust logging, monitoring, alerting, retry, and error-handling mechanisms to ensure high pipeline availability and uptime.Governance & Security: Apply data-quality frameworks, reconciliation controls, lineage tracking, documentation standards, and strict role-based access security.Cross-Functional Collaboration: Partner with solution architects, data analysts, application teams, and business stakeholders to translate complex requirements into scalable data solutions.DevOps & Maintenance: Participate in code reviews, CI/CD deployment pipelines, production support, root-cause troubleshooting, and continuous query/cost optimization.Required QualificationsEducation: Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.Experience: 3–5 years of hands-on experience in data engineering, data integration, or cloud data platform development.Core ETL/ELT: Strong background in designing end-to-end data pipelines and deep familiarity with dimensional modeling and data warehousing concepts.Snowflake Proficiency: Solid hands-on experience with Snowflake, including data loading, complex transformations, query tuning, and virtual warehouse optimization.Azure Data Factory (ADF): Practical experience setting up linked services, datasets, pipelines, triggers, and orchestration.Azure Databricks & PySpark: Hands-on experience with Azure Databricks, Apache Spark/PySpark, notebook workflows, cluster management, and Delta Lake concepts.Programming & Querying: Advanced proficiency in SQL and solid working experience with Python for integrating data from relational databases, flat files, REST APIs, and cloud storage.Version Control & Methodology: Familiarity with Git-based version control, CI/CD practices, Agile/Scrum delivery, and cloud security best practices.Soft Skills: Excellent problem-solving, analytical, troubleshooting, written documentation, and verbal communication skills.Preferred Skills & CertificationsTechnologies: Azure Data Lake Storage Gen2 (ADLS Gen2), Delta Lake, Snowpipe, and dbt (data build tool).Tools: Azure DevOps, Git, and REST API integration.Concepts: Data governance, data lineage, and metadata management.Certifications: Active certifications in Microsoft Azure (e.g., Azure Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a strong plus.How to ApplyIf you meet the requirements above and are looking to join a dynamic, data-driven environment, please submit your updated resume outlining your relevant experience.","datePosted":"2026-10-20T10:41:14.410Z","dateModified":"2026-10-20T10:41:14.410Z","hiringOrganization":{"@type":"Organization","name":"Global Applications Solution","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"79878f7369dbdd4336e8a69e"},"url":"https://jobsearcher.com/jobs/79878f7369dbdd4336e8a69e"}}