Job Summary:
RIT Solutions, Inc. is seeking a Databricks Engineer with Financial Services experience to design, build, and operate data and ML solutions on the Databricks platform. The role involves collaborating with various stakeholders to deliver AI solutions and workflows.
Responsibilities:
• design, build, and operate scalable, secure, and governed data and ML solutions on the Databricks platform on Microsoft Azure
• partner closely with data engineering, CDAIO, architecture, data science, risk/compliance, and business stakeholders to deliver trusted Agentic AI solutions and production-grade AI workflows - leveraging Databricks MLflow, Lakehouse, Lakeflow, Feature Store, Unity Catalog, and Databricks Genie.
Qualifications:
Required:
• 5+ years in data engineering and/or platform engineering with significant hands-on Databricks experience in production.
• Demonstrated experience in Financial Services (banking, capital markets, ABS) with understanding of regulated data environments.
• Strong hands-on expertise with one or more of the following: Databricks Lakehouse architecture and Delta Lake, MLflow (tracking, registry, deployment workflow), Lakeflow (pipeline and workflow patterns), Databricks Feature Store, Unity Catalog (governance, permissions, lineage, auditing), Databricks Genie (enablement aligned to governance).
• Deep proficiency in Python and SQL; strong engineering practices (modular code, testing, code review, documentation).
• Experience on Azure (core services relevant to data platforms), with real-world operation of Azure Databricks.
• Practical expertise with data modeling, data quality management, and performance tuning for large-scale datasets.
Preferred:
• Experience with streaming (e.g., structured streaming patterns) and event-driven architectures.
• Knowledge of enterprise data governance and security controls (RBAC/ABAC patterns, encryption, key management, audit logging).
• Experience implementing CI/CD for Databricks assets (e.g., Git-based workflows, automated deployment, environment promotion).
• Familiarity with data and agent observability tooling and metrics (pipeline health, data freshness, schema drift, cost monitoring).
• Prior experience building reusable feature repositories and standardized ML templates in regulated environments.
Company:
Jobdiva Job Portal: https://www1.jobdiva.com/candidates/myjobs/searchjobsdone.jsp?a=xbjdnwgjodtga1y1im2g881fkkeiwd0775lbvq8yqgps8vb2q36w2vj1ga6xxork&compid=-1 Recruitment (contingency search and campus selection). Founded in 2019, the company is headquartered in Arlington, USA, with a team of 201-500 employees. The company is currently Growth Stage.