We Are: Accenture AI & Data, the people who love using data to tell a story. We’re also the world’s largest team of data scientists and experts in machine learning and AI. A great day for us Solving big problems using the latest tech, serious brain power, and deep knowledge of just about every industry. We believe a mix of data, analytics, automation, and responsible AI can do almost anything—spark digital metamorphoses, widen the range of what humans can do, and breathe life into smart products and services. Want to join our crew of sharp analytical minds? Read on to learn more about this role and who we are looking for.  You Are: As a Data Migration/ Modernization Lead, you will stand up the data services and streaming components of the platform and prove that data can be ingested, processed and consumed to meet critical business needs. You will deploy and configure the database, streaming and processing components, and build the ingestion and transformation pipelines that carry a priority data source through to curated datasets fit for analytical consumption. You will implement data quality validation, register metadata and lineage in the catalogue, and enable analyst and data science access to the curated data. You will collaborate with the Platform / DevOps Consultants that data components are deployed through the same infrastructure-as-code and pipeline discipline as the rest of the platform, and with the Lead Enterprise Architect on data modelling and ontology for the priority domain. In this role, you are expected to be a subject matter expert in your discipline, work independently against a defined architecture, and contribute to team decisions within your area of responsibility. Advanced proficiency in Data Engineering and Pipeline Implementation is required. Advanced proficiency in Streaming Data Architecture is recommended. Deploy and configure the data services and streaming components of the platform. Build scheduled and event-driven ingestion pipelines, including change data capture, where required. Develop transformation logic and business rules to curate raw data into consumable datasets. Implement data quality rules and automated validation across the pipeline Establish metadata, lineage and access registration.You know how to come up with strategies, solutions, and processes for managing enterprise-wide data throughout the data life cycle. Your ability to communicate technical concepts to both technical and non-technical stakeholders make you an invaluable asset to any project.  What You’ll Do: Lead the Technology Solution, Architecture and Delivery of large and/or complex full lifecycle data applications across cloud, hybrid and on-prem landscapes Design and build robust data pipelines using scalable Architecture, tools and techniques to produce high quality data structures Design data solutions, architect data transformation projects, develop solution blueprints and data modernization/migration plans, document, and present recommendations to clients and/or stakeholders. Implement quicker data processing methods and integrate complex business logic compatible with daily or real-time/streaming frameworks Increase automation and scaling of complex data sets based on the customer’s analytic use case, such as structured data delivery for business analysis, daily extraction of mission enabling data for data mining/exploration, and transforming data for applied intelligence to power impactful data visualizations  Drive business and proactive development activities like proposal responses, recruitment, etc.   Role is hybrid