{"schemaVersion":"jobsearcher.job.v1","id":"511ea4d9d246048b05eb8ab7","url":"https://jobsearcher.com/jobs/511ea4d9d246048b05eb8ab7","canonicalUrl":"https://jobsearcher.com/jobs/511ea4d9d246048b05eb8ab7","title":"Databricks Engineer","description":"Infoverity is seeking an experienced Databricks Engineer to join our dynamic consulting team, helping clients architect, build, and optimize modern data platforms. In this role, you will design and implement scalable data solutions, leveraging cloud technologies, specifically Databricks, to drive innovation in AI/ML, data warehousing, and data integration. As a key player at Infoverity you will collaborate with cross-functional teams, including data scientists, business analysts, and solution architects, to deliver high-impact data solutions tailored to our clients’ needs.\nKey Responsibilities Data Engineering & Architecture: Design and implement scalable, cloud-based data pipelines to ingest, transform, and store data from various sources.\nData Warehousing & Integration: Develop and optimize ETL/ELT workflows, ensuring efficient data movement between systems, specifically Databricks.\nAI/ML Enablement: Work alongside data science teams to support feature engineering, model training, and ML operations (MLOps) in cloud environments.\nData Modeling & Governance: Develop data models, schemas, and best practices to ensure data integrity, consistency, and security.\nPerformance Optimization: Monitor, troubleshoot, and optimize query performance, ensuring scalability and efficiency.\nConsulting & Client Engagement: Work directly with clients to understand business needs, recommend best practices, and deliver tailored data solutions.\nData Architecture Design: Design and implement scalable, high-performance data architectures using Databricks.\nRequirement Gathering: Lead requirement-gathering sessions with clients and internal teams to understand business needs and define best practices for solutions including data workflows.\nCloud Collaboration: Collaborate with cloud platform teams to optimize data storage and retrieval in environments like AWS S3, Azure Data Lake, and Delta Lake, among others.\nWorkflow Optimization: Translate complex data processes, such as those in Alteryx and Tableau, into optimized Databricks workflows using PySpark and SQL.\nAutomation Development: Develop reusable automation scripts to streamline workflow migrations and improve operational efficiency.\nDevelopment Support: Provide hands-on development and troubleshooting support to ensure smooth implementation and optimal performance.\nGovernance & Best Practices: Partner with cross-functional teams to establish data governance frameworks, best practices, and standardized reporting processes.\nTraining & Support: Deliver training, documentation, and ongoing support to empower users and enhance organizational data literacy.\nRequirements Required Qualifications\nMinimum of 2 to 3 years of experience in data engineering, data architecture, and data integration.\nStrong expertise in Databricks, Snowflake, and/or Microsoft Fabric.\nProficiency in SQL, Python, Spark, and distributed data processing frameworks.\nExperience with cloud platforms (Azure, AWS, or GCP) and their native data services.\nHands-on experience with ETL/ELT development, data pipelines, and data warehousing.\nKnowledge of AI/ML workflows, including feature engineering and ML model deployment.\nStrong understanding of data governance, security, and compliance best practices.\nExcellent problem-solving, communication, and client-facing consulting skills.\nAbility to work independently and as part of a team.\nPreferred Qualifications Certifications in Databricks, Snowflake, Microsoft Fabric, or a cloud platform (Azure, AWS, GCP).\nExperience with Apache Airflow, dbt, Delta Lake, or similar data orchestration tools.\nFamiliarity with DevOps, CI/CD pipelines, and Infrastructure as Code (IaC) tools like Terraform.\nSeniority level Mid-Senior level\nEmployment type Full-time\nJob function Information Technology\nIndustries IT Services and IT Consulting\nWe’re helping you find new opportunities. Referrals increase your chances of interviewing at Infoverity.\n\n#J-18808-Ljbffr","company":"Infoverity","rawCompany":"infoverity","city":"Dublin","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-07-16T03:29:25.262Z","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":"15-1243.00","title":"Database Architects","slug":"database-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":"Databricks Engineer","description":"Infoverity is seeking an experienced Databricks Engineer to join our dynamic consulting team, helping clients architect, build, and optimize modern data platforms. In this role, you will design and implement scalable data solutions, leveraging cloud technologies, specifically Databricks, to drive innovation in AI/ML, data warehousing, and data integration. As a key player at Infoverity you will collaborate with cross-functional teams, including data scientists, business analysts, and solution architects, to deliver high-impact data solutions tailored to our clients’ needs.\nKey Responsibilities Data Engineering & Architecture: Design and implement scalable, cloud-based data pipelines to ingest, transform, and store data from various sources.\nData Warehousing & Integration: Develop and optimize ETL/ELT workflows, ensuring efficient data movement between systems, specifically Databricks.\nAI/ML Enablement: Work alongside data science teams to support feature engineering, model training, and ML operations (MLOps) in cloud environments.\nData Modeling & Governance: Develop data models, schemas, and best practices to ensure data integrity, consistency, and security.\nPerformance Optimization: Monitor, troubleshoot, and optimize query performance, ensuring scalability and efficiency.\nConsulting & Client Engagement: Work directly with clients to understand business needs, recommend best practices, and deliver tailored data solutions.\nData Architecture Design: Design and implement scalable, high-performance data architectures using Databricks.\nRequirement Gathering: Lead requirement-gathering sessions with clients and internal teams to understand business needs and define best practices for solutions including data workflows.\nCloud Collaboration: Collaborate with cloud platform teams to optimize data storage and retrieval in environments like AWS S3, Azure Data Lake, and Delta Lake, among others.\nWorkflow Optimization: Translate complex data processes, such as those in Alteryx and Tableau, into optimized Databricks workflows using PySpark and SQL.\nAutomation Development: Develop reusable automation scripts to streamline workflow migrations and improve operational efficiency.\nDevelopment Support: Provide hands-on development and troubleshooting support to ensure smooth implementation and optimal performance.\nGovernance & Best Practices: Partner with cross-functional teams to establish data governance frameworks, best practices, and standardized reporting processes.\nTraining & Support: Deliver training, documentation, and ongoing support to empower users and enhance organizational data literacy.\nRequirements Required Qualifications\nMinimum of 2 to 3 years of experience in data engineering, data architecture, and data integration.\nStrong expertise in Databricks, Snowflake, and/or Microsoft Fabric.\nProficiency in SQL, Python, Spark, and distributed data processing frameworks.\nExperience with cloud platforms (Azure, AWS, or GCP) and their native data services.\nHands-on experience with ETL/ELT development, data pipelines, and data warehousing.\nKnowledge of AI/ML workflows, including feature engineering and ML model deployment.\nStrong understanding of data governance, security, and compliance best practices.\nExcellent problem-solving, communication, and client-facing consulting skills.\nAbility to work independently and as part of a team.\nPreferred Qualifications Certifications in Databricks, Snowflake, Microsoft Fabric, or a cloud platform (Azure, AWS, GCP).\nExperience with Apache Airflow, dbt, Delta Lake, or similar data orchestration tools.\nFamiliarity with DevOps, CI/CD pipelines, and Infrastructure as Code (IaC) tools like Terraform.\nSeniority level Mid-Senior level\nEmployment type Full-time\nJob function Information Technology\nIndustries IT Services and IT Consulting\nWe’re helping you find new opportunities. Referrals increase your chances of interviewing at Infoverity.\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T03:29:25.262Z","dateModified":"2026-07-16T03:29:25.262Z","hiringOrganization":{"@type":"Organization","name":"Infoverity","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dublin","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"511ea4d9d246048b05eb8ab7"},"url":"https://jobsearcher.com/jobs/511ea4d9d246048b05eb8ab7"}}