Our client is looking for a Data Engineer
The Sr. Azure Data Engineer will lead the creation of high-value data-driven solutions leveraging our client’s proven implementation methodology and solutions for enterprise projects. You will also contribute to technical pre-sales activities as required. Responsibilities include designing solution architecture, defining requirements, and leading the project delivery team. You will work collaboratively across all sales, service delivery, and project management organizations to serve clients.
The ideal candidate will have extensive experience with Microsoft/Azure data services and Databricks technology. Proficiency with the Databricks platform and implementing enterprise Data Lakehouse is required. Candidates will be expected to contribute to all stages of the data lifecycle including data ingestion, data modeling, data profiling, data quality, data transformation, data movement, and data curation.
Key Responsibilities:
- Lead and manage the development of large-scale data warehouse solutions.
- Translate business requirements into functional and technical requirements.
- Design, develop, and maintain data pipelines using Databricks and Microsoft Azure services.
- Solution Azure Cloud-based enterprise data architectures.
- Automate data pipelines and processes.
- Engage directly with client stakeholders, managers, and end-users.
- Collaborate with the Cyclotron team including Project Managers, Software Engineers, and Business Analysts.
PLACEMENT CRITERIA & REQUIREMENTS:
- Focus on Azure data engineering solutions.
- 8+ years of data engineering delivery experience.
- 3+ years of Databricks engineering development experience.
- 2+ years of technical team leadership or technical management experience.
- Current Azure and/or Databricks certifications.
TECHNICAL SKILLS REQUIRED:
- General Architecture:
- Design large-scale data warehouse solutions.
- Interpret business requirements into functional and technical requirements.
- Develop and maintain data pipelines using Databricks and Microsoft Azure services.
- Solution Azure Cloud-based enterprise data architectures.
- Automate data pipelines.
- Information Architecture:
- Data Modeling principles for relational and dimensional data structures.
- Data Warehouse design principles.
- Data Lake design principles, Data Virtualization.
- Hybrid enterprise data architecture.
- Strong knowledge of data warehouse concepts and T-SQL relational/non-relational databases for data access and Advanced Analytics.
- Experience with Python, SQL, DAX, M.
- Reporting and data visualization tools, specifically PowerBI.
- Practical knowledge of Microsoft SQL Server.
- Experience in multidimensional and/or tabular models (SSAS).