Accenture is stepping boldly into a new Data & AI decade that will reshape work and society, aiming to help clients optimize and reinvent their business with data & AI.
Requirements
- Minimum of 5 years of hands-on experience on Cloud and Big Data technologies such serverless data processing, Spark/SparkSQL, batch and streaming services, event-driven data pipelines, cloud databases, and programming languages such as Python, TSQL, JSON, and XML.
- Minimum 3 years of experience in following: MSSQL, Azure Synapse, Azure Data Factory, Azure Storage, Azure DevOps, Power BI, Databricks, Cosmos DB, VS Code, VSTS SQL Project.
- Minimum 3 years of experience in Cloud data storage, data management and data services
- Minimum 3 years of experience in Data supply chain including streaming pipelines to help address the challenges of acquiring data, evaluating its value, distilling & analyzing.
- Minimum 3 years of experience to Examine data from multiple sources, and share insights which provide competitive advantage
- Minimum 2 years of experience with Devops and CI/CD processes
- Minimum 2 years of experience with Scheduling and orchestration
Responsibilities
- Apply data engineering principles to create reusable workflows for data ingestion, quality assurance, transformation, and optimization.
- Design, Build and test scalable data pipelines using extract, transform, and load tools.
- Document requirements and technical design documents.
- Migrate data from legacy data warehouses using cloud architecture principles
- Automate the flow of data for consumption.
- Build business processes that enable data governance.
- Design and advise on data quality rules and set up effective data compliance policies.
Other
- Collaborate seamlessly across cross-functional teams to ensure alignment and integration.
- Mentor and support junior team members, fostering growth and technical excellence.
- Establish and uphold technical standards and best practices across projects.
- Ability to lead and effectively facilitate design sessions with business customers and the BI team to derive data requirements and data design information
- Business acumen and domain knowledge to catch nuances in the meaning of the data, collaborate with cross-functional teams to better understand their areas of expertise, and communicate effectively with their leadership teams.
