We are seeking an experienced Senior Databricks Consultant to join our DXC Microsoft Practice, working across enterprise clients to deliver modern data, analytics, and AI solutions on the Azure platform. This is an exciting opportunity to play a key role in shaping scalable, cloud-native data platforms using Azure Databricks, Microsoft Fabric, and modern data engineering practices, helping customers unlock value from their data through advanced analytics, machine learning, and real‐time insights.
Role
Design, build, and optimise scalable data pipelines and data processing solutions using Azure Databricks.
Work within the Microsoft Azure ecosystem, integrating services such as Data Lake, Synapse, Data Factory, and Fabric.
Translate business and analytics requirements into robust technical data solutions.
Develop ETL/ELT workflows using Spark (PySpark, Scala, or SQL).
Support architecture design for modern cloud data platforms, ensuring scalability, performance, and security.
Collaborate with data engineers, solution architects, and business stakeholders to deliver end‐to‐end solutions.
Implement data modelling, data quality, and governance best practices.
Enable advanced analytics and AI/ML use cases using Databricks ML capabilities.
Contribute to presales activities, solution shaping, and client workshops.
Provide technical leadership and mentorship to junior consultants and engineers.
Ensure solutions align with Microsoft best practices and enterprise governance standards.
Experience
Strong experience in data engineering, analytics, or cloud consulting roles.
Strong hands‐on experience with Databricks (Azure Databricks preferred).
Solid understanding of Apache Spark, PySpark, SQL, and distributed data processing.
Experience within the Microsoft Azure data ecosystem (Data Lake, Synapse, Data Factory, Fabric).
Strong knowledge of data architecture, data modelling, and ETL/ELT design patterns.
Experience working in consulting or client‐facing delivery environments.
Ability to translate business requirements into technical data solutions.
Strong communication skills and ability to engage both technical and non‐technical stakeholders.
Exposure to CI/CD, DevOps, or Infrastructure‐as‐Code is highly desirable.
Experience with Python and/or Scala is advantageous.
Understanding of data governance, security, and compliance in enterprise environments.
Microsoft certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect).
Experience with machine learning workflows in Databricks.
Experience with Microsoft Fabric and OneLake.
Exposure to real‐time streaming data pipelines (Event Hubs, Kafka).
Experience in regulated industries such as finance, government, or insurance.
Pre‐sales or solution shaping experience in consulting environments.
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