Senior Associate

Not Applicable Data, Analytics & AI Senior Associate A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers.

• Analyses current business practices, processes, and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services.
• Provide technical leadership and thought leadership as a senior member of the Analytics Practice in areas such as data access & ingestion, data processing, data integration, data modeling, database design & implementation, data visualization, and advanced analytics.
• Engage and collaborate with customers to understand business requirements/use cases and translate them into detailed technical specifications.
• Develop best practices including reusable code, libraries, patterns, and consumable frameworks for cloud-based data warehousing and ETL.
• Maintain best practice standards for the development or cloud-based data warehouse solutioning including naming standards.
• Designing and implementing highly performant data pipelines from multiple sources using Apache Spark and/or Azure Databricks
• Integrating the end-to-end data pipeline to take data from source systems to target data repositories ensuring the quality and consistency of data is always maintained
• Working with other members of the project team to support delivery of additional project components (API interfaces)
• Evaluating the performance and applicability of multiple tools against customer requirements
• Working within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints.
• Integrate Databricks with other technologies (Ingestion tools, Visualization tools).
• Proven experience working as a data engineer
• Highly proficient in using the spark framework (python and/or Scala)
• Extensive knowledge of Data Warehousing concepts, strategies, methodologies.
• Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably in Databricks).
• Hands on experience designing and delivering solutions using Azure including Azure Storage, Azure SQL Data Warehouse, Azure Data Lake, Azure Cosmos DB, Azure Stream Analytics
• Experience in designing and hands-on development in cloud-based analytics solutions.
• Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service is required.
• Designing and building of data pipelines using API ingestion and Streaming ingestion methods.
• Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential.
• Thorough understanding of Azure Cloud Infrastructure offerings.
• Strong experience in common data warehouse modeling principles including Kimball.
• Working knowledge of Python is desirable
• Experience developing security models.
• Databricks & Azure Big Data Architecture Certification would be plus
• Must be team oriented with strong collaboration, prioritization, and adaptability skills required

Degrees/Field of Study required Bachelor of Engineering, Bachelor of Technology, Master of Engineering Degrees/Field of Study preferred Azure Data Factory, Data Engineering, Microsoft Azure Databricks