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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Databricks Platform & Data Engineer - **Company:** PROPERTY CONSULTANT FIN SVC - **Location:** Plano, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Flow Control, Python (Programming Language), Raw Data, Software Deployment, Data Streaming, Google Cloud, Apache Spark, Data Lakes, Data Lineage, Deployment Automation, Apache Kafka, Data Management, Machine Learning Operations, Databricks - **Published:** June 26, 2026 - **Apply:** https://www.dice.com/job-detail/89615815-94a8-4ea8-b8eb-07d4505326da ## About the Role Seeking a senior Databricks Platform & Data Engineer to join our Databricks Center of Excellence (CoE). This role blends platform engineering, architecture, and hands-on data engineering, with a focus on building and scaling enterprise-grade Databricks environments for large, regulated clients. The ideal candidate will lead platform setup, governance, and adoption, while partnering directly with clients to design and deliver high-impact use cases leveraging the latest Databricks capabilities (e.g., Dataflow, Unity Catalog, AI/BI, Genie). This is a client-facing consulting role requiring strong technical depth, communication skills, and the ability to translate business requirements into scalable data platform solutions., 12+ years of experience in data engineering, platform engineering, or data architecture 5+ years hands-on experience with Databricks in large enterprise environments Deep expertise in: - * Apache Spark (Scala/Python) * Delta Lake and Lakehouse architectures * Databricks workspace setup, cluster policies, and job orchestration * Strong experience with cloud platforms (AWS, Azure, or Google Cloud Platform) * Experience implementing data governance, security, and compliance controls * Proven ability to design and deliver scalable, production-grade data platforms * Strong client-facing and communication skills Preferred Qualifications: Experience in financial services or other regulated industries Familiarity with data governance frameworks, regulatory reporting, and risk data environments Databricks certifications (e.g., Data Engineer, Solutions Architect) Experience with: Real-time streaming (Kafka, Structured Streaming) MLOps / Model Serving Data marketplace / data product architectures ## Description Platform Engineering & Architecture Design and deploy enterprise-scale Databricks Lakehouse platforms across AWS/Azure Establish secure, governed environments using Unity Catalog, role-based access controls, and data lineage Define platform standards, reusable patterns, and guardrails for scalable adoption Optimize platform performance, cost, and reliability for production workloads Implement CI/CD, environment promotion, and DevOps automation for Databricks Databricks Feature Enablement Lead adoption of modern Databricks capabilities including: Unity Catalog: Centralized governance, access control, lineage Dataflow / declarative pipelines: build scalable ingestion and transformation frameworks Genie / AI-assisted development: accelerate developer productivity and data accessibility Enable AI/BI dashboards, model serving, and advanced analytics use cases Data Engineering & Use Case Delivery Build and optimize batch and streaming data pipelines using Spark and Delta Lake Develop data products and domain-oriented pipelines aligned to enterprise data strategies Lead end-to-end use case delivery, from requirements to production deployment Drive data quality, observability, and pipeline reliability Client Engagement & Advisory Act as a trusted advisor to client stakeholders (architecture, data, risk, and business teams) Translate business requirements into technical architecture and delivery roadmaps Lead workshops, solution design sessions, and platform adoption strategies Support proposals, solutioning, and client innovations within regulated industries CoE Contribution: Build and contribute to NTT DATA accelerators, frameworks, and reusable assets Define best practices, reference architectures, and playbooks for enterprise Databricks adoption Mentor junior engineers and support capability building across the CoE ## Related Videos - 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