Azure Data Bricks Engineer

Overview

Remote
Depends on Experience
Full Time

Skills

Azure Data Factory (ADF)
Databricks
ADLS
Azure Analysis Services
Power BI
Azure Monitor
NoSQL storage design; data modeling (normalized
star
snowflake schemas)
EDW
ODS

Job Details

Azure Data Bricks Engineer

Type : Remote

Must-Have Technical Skills

  1. Azure Data Services Expertise: Azure Synapse (mandatory), Azure Data Factory (ADF), Databricks, ADLS, Azure Analysis Services, Power BI, and Azure Monitor.
  2. Data Architecture & Modeling: Strong experience in dimensional, relational, and NoSQL storage design; data modeling (normalized, star, snowflake schemas), EDW & ODS.
  3. Cloud Data Implementation: Proven experience in designing and implementing secure, scalable cloud data solutions on Azure; familiarity with MPP architectures.
  4. Data Integration & Processing: ETL (batch and real-time), streaming services, and integration techniques for large-scale data flows.
  5. Data Lake & Cloud Warehouse: Hands-on experience with ADLS and Azure Synapse; working knowledge of Snowflake and AWS Lake Formation.
  6. Master Data Management: Expertise in MDM and reference data management practices.

Roles & Responsibilities

  1. 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.
  2. Collaborate with Enterprise Architects to define and implement high-level architecture aligned with organizational standards.
  3. Plan and Optimize Azure Infrastructure Capacity in partnership with Stryker s architecture team to ensure scalability and performance.
  4. Conduct Design and Solution Reviews to validate technical approaches and ensure best practices.
  5. Translate Business Requirements into Technical Solutions by working closely with business stakeholders and business analysts.
  6. Coordinate with Technical Leads for ETL, reporting, and data modeling to deliver robust and efficient solutions.
  7. Provide Technical Guidance to project teams, resolving challenges and ensuring successful execution throughout the project lifecycle.
  8. Understand Business Context and Reporting Needs to design and model analytical cubes that meet functional requirements.
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