US E-Consulting Services - Azure Databricks Developer - Managed Services Engineer III

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Azure Databricks Developer you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

 Work you’ll do/Responsibilities  

We are looking for an experienced Azure Databricks Developer to join our data engineering team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and analytics solutions on the Azure platform. You will work closely with data scientists, analysts, and other engineers to enable data-driven innovation and decision-making across the organization..

• Design and implement data ingestion, processing, and transformation pipelines using Azure Databricks.
• Develop and optimize Spark jobs for performance and cost-efficiency.
• Build and manage data lakes and data warehouses in Azure.
• Implement data quality checks and monitoring to ensure data accuracy and reliability.
• Collaborate with data scientists to productionize machine learning models.
• Provide technical guidance and support to other team members.Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to provide clear guidance to others
• Provide training and support to end-users on how to leverage Power BI tools.
• Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
• Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

AI & Engineering - Industry Solutions teams works with the Customer group to bring a flexible capability and fluid capacity model to the delivery of small technology projects and enhancements.

Qualifications

Required

• 6 years of experience in data engineering or a similar role.
• Hands-on experience with Azure Databricks and Apache Spark.
• Proficiency in languages such as Python, Scala, or SQL.
• Experience with other Azure data services like Azure Data Lake Storage, Azure Data Factory, and Azure Synapse Analytics.
• Strong understanding of data warehousing concepts and ETL/ELT processes
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
• Limited immigration sponsorship may be available
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve

Preferred

• Microsoft Certified: Data Analyst Associate certification.
• Experience with the broader Microsoft Azure Data Stack (e.g., Azure Data Factory, Synapse Analytics).
• Background in data warehousing concepts and dimensional modeling.