Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services - all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 738,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Learn more about how we are measuring value in all directions with Accenture's 360 degree Value Integrated Reporting. About you: As a Databricks Data Engineer, you will play a key role in designing, implementing, and maintaining data pipelines on the Databricks platform that support business and technology objectives. Your primary focus will be on building scalable and efficient data ingestion, transformation, and processing solutions to support our data-driven initiatives. You enjoy working both autonomously and as part of a team and have the confidence to influence and communicate with stakeholders at all levels, and to work in a fast-paced complex environment. About the role: You will be working on client projects with teams from across our Modern Data Platform and Applied Intelligence practice alongside our industry, functional and technology SMEs on some of our clients most challenging projects. From day one, you will be involved in the design and implementation of complex data solutions ranging from batch to streaming and event-driven architectures, across cloud, on-premise and hybrid client technology landscapes. We are looking for 3 years of experience in data engineering in a customer or business facing capacity and experience in the following: Preferred Ability to understand and articulate requirements to technical and non-technical audiences Stakeholder management and communication skills, including prioritising, problem solving and interpersonal relationship building Experiences with design, develop, and implement end-to-end data engineering solutions using Databricks for large-scale data processing and data integration projects. Build and optimize data ingestion processes from various sources, ensuring data quality, reliability, and scalability. Perform data transformation tasks, including data cleansing, aggregation, enrichment, and normalization, using Databricks and related technologies. Monitor and troubleshoot data pipelines, identifying and resolving performance issues, data quality problems, and other technical challenges. Implement best practices for data governance, data security, and data privacy within the Databricks environment. Strong SQL, Python, PySpark knowledge Collaborate with DevOps and infrastructure teams to optimize the performance and scalability of Databricks clusters and resources. Provide guidance and mentorship to junior data engineers, fostering a culture of knowledge sharing and continuous learning within the team. Desirable Knowledge in DataOps and experience in delivering CI/CD and DevOps capabilities in a data environment Experience with advanced analytics and machine learning frameworks such as Apache Spark MLlib, TensorFlow, or PyTorch. Proficiency in data visualization tools such as Tableau, Power BI, or Looker Certification in Databricks Engineer Professional would be a plus. 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