Azure Databricks Engineer

Azure Databricks

Must-Have Technical Skills
• zure Data Services Expertise: Azure Synapse (mandatory), Azure Data Factory (ADF), Databricks, ADLS, Azure Analysis Services, Power BI, and Azure Monitor.
• Data Architecture & Modeling: Strong experience in dimensional, relational, and NoSQL storage design; data modeling (normalized, star, snowflake schemas), EDW & ODS.
• Cloud Data Implementation: Proven experience in designing and implementing secure, scalable cloud data solutions on Azure; familiarity with MPP architectures.
• Data Integration & Processing: ETL (batch and real-time), streaming services, and integration techniques for large-scale data flows.
• Data Lake & Cloud Warehouse: Hands-on experience with ADLS and Azure Synapse; working knowledge of Snowflake and AWS Lake Formation.
• Predictive Analytics & ML: Basic understanding of statistical modeling, linear/logistic regression, and exploratory data analysis.
• Master Data Management: Expertise in MDM and reference data management practices.

Must-Have Functional Skills
• Domain Knowledge: Deep understanding of upstream systems such as ERP, CRM, Sales Operations (territory/quota management), pricing, contract management, and master data systems.
• End-to-End Architecture Design: Ability to design high-level and low-level solutions, including data management and processing flows.
• Business Intelligence & Analytics: Strong background in BI solution design, data profiling, and reporting requirements.
• Collaboration & Integration: Work closely with enterprise architects, technical leads, and cross-functional teams to integrate technology and functionality.
• Solution Review & Governance: Conduct design reviews, ensure compliance with governance standards, and accommodate feedback from stakeholders.
• Communication & Leadership: Clear communication between business stakeholders and IT teams; ability to guide teams through technical challenges.

Roles & Responsibilities
• Design and Architect BI Solutions leveraging Azure analytics services such as Azure Data Factory (ADF), Databricks, Data Lake, Power BI, Automation, Azure AD, Azure Monitor, Azure Analysis Services, Synapse, and advanced capabilities like predictive analytics and machine learning.
• Collaborate with Enterprise Architects to define and implement high-level architecture aligned with organizational standards.
• Plan and Optimize Azure Infrastructure Capacity in partnership with Stryker's architecture team to ensure scalability and performance.
• Conduct Design and Solution Reviews to validate technical approaches and ensure best practices.
• Translate Business Requirements into Technical Solutions by working closely with business stakeholders and business analysts.
• Coordinate with Technical Leads for ETL, reporting, and data modeling to deliver robust and efficient solutions.
• Provide Technical Guidance to project teams, resolving challenges and ensuring successful execution throughout the project lifecycle.
• Understand Business Context and Reporting Needs to design and model analytical cubes that meet functional requirements.

Generic Managerial Skills, If any
• Stakeholder & Communication Management - Engage with business and technical teams, translating complex data concepts into clear business language.
• Project & Resource Leadership - Plan, prioritize, and oversee data architecture initiatives, ensuring timely delivery and optimal resource utilization.
• Strategic & Risk Management - Align data strategies with business objectives while identifying and mitigating architectural risks.
• Governance & Compliance Oversight - Ensure adherence to data governance, security, and regulatory standards across projects.