{"schemaVersion":"jobsearcher.job.v1","id":"51e87d3bdce89a387b3e89bb","url":"https://jobsearcher.com/jobs/51e87d3bdce89a387b3e89bb","canonicalUrl":"https://jobsearcher.com/jobs/51e87d3bdce89a387b3e89bb","title":"Data Engineer","description":"Responsibilities Include\nData Engineering & Architecture\nBuild and maintain data mart solutions that support reporting and analytics use cases.\nDesign, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. Develop and troubleshoot ETL/ELT logic using SQL and team tooling.\nDesign and build dimensional data models, including facts and dimensions, determine appropriate table grain, and implement slowly changing dimensions where historical tracking is required.\nDefine and implement practical data retention and history strategies that preserve analytical value without overloading downstream reporting tools.\nData Quality, Reliability & Operations\nImplement and maintain data quality controls, reconciliation checks, testing, and monitoring to ensure data accuracy, consistency, and reliability.\nSupport production reliability through job monitoring, issue resolution, root-cause analysis, operational support, and documentation.\nCreate and maintain production support and deployment artifacts.\nCollaboration & Delivery\nCollaborate with business stakeholders and technical teams to translate business needs into scalable technical solutions, including metric logic, and data definitions.\nWork closely with development partners, product owners, and team members to design features, decompose stories, and prioritize delivery.\nShare technical knowledge and support team success through collaboration, documentation, and guidance.\nLeadership & Influence\nProvide technical leadership for data pipeline development and engineering practices.\nNavigate cross-functional communication effectively to maintain alignment across teams.\nUse data-driven reasoning to constructively challenge decisions, align on outcomes, and execute once direction is set.\nRisk, Governance, & Continuous Improvement\nIdentify technology risks and dependencies early and help establish mitigation plans.\nImplement data security, governance, and metadata management practices to protect sensitive information.\nContribute to a culture of open feedback, accountability, and continuous improvement.\nWhat you have\nRequired Qualifications\nExpertise in ETL/ELT development, SQL, and data engineering best quality practices including data quality, testing, monitoring, and exception handling.\nStrong understanding of data pipelines, data mart design, and common engineering patterns.\nStrong understanding of data warehouse concepts, including star schema, fact and dimension modeling, table grain, slowly changing dimensions, and operational data stores.\nExperience with Google Cloud technologies, including BigQuery and Cloud Storage.\nBusiness analysis experience to translate business requirements into data mappings, metric logic, and data definitions, and to perform data analysis.\nMinimum of 3 years of hands-on data engineering experience.\nSolid understanding of the data lifecycle, metadata management, and governance standards.\nAbility to recommend practical data retention and history strategies that balance analytical value with reporting performance.\nStrong cross-functional collaboration skills with leadership, colleagues, and stakeholders.\nStrong communication and stakeholder management skills across technical and non-technical audiences.\nWillingness to learn new skills and adapt to evolving technologies to meet future business needs.\nProficiency with development tools including version control (for example, GitHub), project management software (for example, JIRA), and orchestration tools (for example, Control-M, SQL Server Integration Services, Informatica, or similar).\nBachelor’s or master’s degree in computer science, information technology, or a related field, or equivalent practical experience.\nPreferred Competencies\n5+ years of experience with reporting and data visualization tools (Power BI, Tableau)\n5+ years of experience with data management tools and coding languages (Python)\n3+ years of experience in the financial services industry and/or a B2B environment\nExperience leveraging AI in development lifecycle, and enabling AI-ready data environments.\nPay: $30.00 - $45.00 per hour\nWork Location: In person","company":"Bharathvio Technologies","rawCompany":"bharathvio technologies","city":"Kent","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-08-04T19:26:47.510Z","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":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Responsibilities Include\nData Engineering & Architecture\nBuild and maintain data mart solutions that support reporting and analytics use cases.\nDesign, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. Develop and troubleshoot ETL/ELT logic using SQL and team tooling.\nDesign and build dimensional data models, including facts and dimensions, determine appropriate table grain, and implement slowly changing dimensions where historical tracking is required.\nDefine and implement practical data retention and history strategies that preserve analytical value without overloading downstream reporting tools.\nData Quality, Reliability & Operations\nImplement and maintain data quality controls, reconciliation checks, testing, and monitoring to ensure data accuracy, consistency, and reliability.\nSupport production reliability through job monitoring, issue resolution, root-cause analysis, operational support, and documentation.\nCreate and maintain production support and deployment artifacts.\nCollaboration & Delivery\nCollaborate with business stakeholders and technical teams to translate business needs into scalable technical solutions, including metric logic, and data definitions.\nWork closely with development partners, product owners, and team members to design features, decompose stories, and prioritize delivery.\nShare technical knowledge and support team success through collaboration, documentation, and guidance.\nLeadership & Influence\nProvide technical leadership for data pipeline development and engineering practices.\nNavigate cross-functional communication effectively to maintain alignment across teams.\nUse data-driven reasoning to constructively challenge decisions, align on outcomes, and execute once direction is set.\nRisk, Governance, & Continuous Improvement\nIdentify technology risks and dependencies early and help establish mitigation plans.\nImplement data security, governance, and metadata management practices to protect sensitive information.\nContribute to a culture of open feedback, accountability, and continuous improvement.\nWhat you have\nRequired Qualifications\nExpertise in ETL/ELT development, SQL, and data engineering best quality practices including data quality, testing, monitoring, and exception handling.\nStrong understanding of data pipelines, data mart design, and common engineering patterns.\nStrong understanding of data warehouse concepts, including star schema, fact and dimension modeling, table grain, slowly changing dimensions, and operational data stores.\nExperience with Google Cloud technologies, including BigQuery and Cloud Storage.\nBusiness analysis experience to translate business requirements into data mappings, metric logic, and data definitions, and to perform data analysis.\nMinimum of 3 years of hands-on data engineering experience.\nSolid understanding of the data lifecycle, metadata management, and governance standards.\nAbility to recommend practical data retention and history strategies that balance analytical value with reporting performance.\nStrong cross-functional collaboration skills with leadership, colleagues, and stakeholders.\nStrong communication and stakeholder management skills across technical and non-technical audiences.\nWillingness to learn new skills and adapt to evolving technologies to meet future business needs.\nProficiency with development tools including version control (for example, GitHub), project management software (for example, JIRA), and orchestration tools (for example, Control-M, SQL Server Integration Services, Informatica, or similar).\nBachelor’s or master’s degree in computer science, information technology, or a related field, or equivalent practical experience.\nPreferred Competencies\n5+ years of experience with reporting and data visualization tools (Power BI, Tableau)\n5+ years of experience with data management tools and coding languages (Python)\n3+ years of experience in the financial services industry and/or a B2B environment\nExperience leveraging AI in development lifecycle, and enabling AI-ready data environments.\nPay: $30.00 - $45.00 per hour\nWork Location: In person","datePosted":"2026-08-04T19:26:47.510Z","dateModified":"2026-08-04T19:26:47.510Z","hiringOrganization":{"@type":"Organization","name":"Bharathvio Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Kent","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"51e87d3bdce89a387b3e89bb"},"url":"https://jobsearcher.com/jobs/51e87d3bdce89a387b3e89bb"}}