Senior Analytics Engineer

About Onix: Onix is a trusted cloud consulting company that helps companies get the most out of their technology with cloud-powered solutions, best-in-class services, and the Datametica Birds, data migration products that unleash AI potential. We are able to deliver exceptional results for our customers because of our 20 years of cloud experience, depth of technology expertise, and IP-driven data and AI solutions. We offer solutions across a wide range of use cases and industries that are tailored to the unique needs of each customer. From advanced cloud security solutions to innovative AI capabilities and data migration products, we have you covered. Our global team of experts are the most reliable, talented and knowledgeable in the industry. Summary: Onix is seeking experienced Senior Analytics Engineer with a proven track record in production-level dbt implementations to join our delivery team. Ideal candidates will strongly understand dbt, Lakehouse Architecture, data modeling, data management, and Continuous Integration/Deployment with dbt. We are seeking individuals with substantial experience with dbt and Databricks. Location: Remote - US, Support EST business hours Primary Responsibilities: Lead the design, development, and implementation of enterprise-level analytics engineering solutions, including, but not limited to, Lakehouse & data warehouse and other cloud-based data environments that integrate with an overall data architecture. Provide thought leadership and technical expertise in designing, building, and optimizing end-to-end data pipelines, from data extraction and transformation to loading and visualization. Collaborate with business stakeholders, data engineers, data scientists, and other teams to understand data requirements, use cases, and business objectives. Design and implement efficient and robust data pipelines, ETL processes, and data integration workflows using dbt, Databricks, and related technologies. Optimize and tune data processing frameworks, data ingestion mechanisms, and data storage strategies for performance and cost efficiency. Ensure data quality, integrity, and governance standards are met throughout the data lifecycle. Create and maintain technical documentation, run books, code, and best practices for analytics engineering. Stay up-to-date with the latest advancements in dbt and Databricks. Consult on Professional Services Engagements to help our customers design and implement data warehouse and data lakehouse solutions. Lead and develop best practices for the larger data analytics delivery team. Provide client presentations to review project design, outcomes, and recommendations. Preferred Qualifications & Skills. 5 years experience in data warehousing, analytics engineering & analytics in areas such as query performance tuning and ELT/ETL pipelines. 5 years experience writing complex SQL to support business intelligence. Experience with building dimensionalstar schema data models. In-depth knowledge of dbt, including but not limited to: Models, Snapshots, Seeds, Data Quality Tests, and Production Workflows. General understanding of Databricks and its components, such as Unity Catalog, Delta Lake, Delta Live Tables, Apache Spark. Experience with Terraform, Git, CI/CD tools, as well as Automation and Integration testing. Experience with common Business Intelligence (BI) tools and frameworks, including, but not limited to, Looker, Tableau or other, equivalent technologies. Possess strong problem-solving and analytical skills, with the ability to identify and resolve complex analytics engineering challenges. Has excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders. Can rapidly adapt to changing project