Responsibilities:
* Architect and implement scalable and resilient data pipelines, ensuring efficient data ingestion, processing, and storage in a cloud environment.
* Coordinate cross-functional teams, including business leads, system owners, architects, engineers, and external vendors to deliver high impact solutions.
* Develop and enforce policies and procedures for data management, ensuring the integrity and confidentiality of sensitive data.
* Develop and implement the strategic vision for the data analytics platform, ensuring alignment with organizational goals and objectives.
* Enhance cloud capabilities by developing and implementing cloud application patterns, automating cloud services using infrastructure as code tools such as CloudFormation and Terraform.
* Lead the design, development, and maintenance of a robust cloud data platform architecture, leveraging Databricks Lakehouse, AI, and ML technologies.
* Manage a portfolio of data analytics projects, ensuring they are delivered on time, within scope, and budget.
* Oversee the creation of blueprints, roadmaps, and reference architectures for the data analytics infrastructure and services.
* Oversee the integration of diverse data sources, ensuring data quality and consistency, and facilitate the transformation of data into actionable insights through AI and ML models.
* Provide expert guidance on data warehouse solutions, advanced analytics, data modeling, and the implementation of Databricks Lakehouse.
* Utilize modern cloud application architectures, including microservices, containerization, and serverless computing, to optimize performance and cost-efficiency.
Skills:
* Conduct research and stay up-to-date with the latest advancements in GenAI, Azure, OpenAI, AWS, and Google GenAI technologies.
* Deep understanding of machine learning (MLOps), data visualization (e.g., PowerBI, Tableau), and event-driven architecture.
* Design, develop, and implement GenAI solutions that integrate with Azure and OpenAI platforms.
* Experience in data modelling, data transformation, and statistical computing (e.g., R, Python).
* Experience with AWS services, such as Amazon SageMaker, AWS Lambda, and AWS AI/ML services.
* Experience with cloud-based deployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.
* Expertise in cloud-native technologies and services, including microservices, serverless computing, and containerization (e.g., Docker, Kubernetes).
* Knowledge of Google Cloud services, including Google Cloud AI Platform, Google Cloud Functions, and Google Cloud AutoML.
* Proficiency in databases (e.g., Oracle, MS SQL, MySQL, Teradata, Databricks), data repositories (e.g., data lakes, data marts).
* Strong knowledge of cloud data platforms, including architecture design, data integration, and the implementation of scalable data pipelines.
Requirements:
* Minimum of 10 years of experience in data analytics, with at least 5 years in a management role managing large-scale data analytics projects.
* Ability to troubleshoot complex technical issues related to AI model deployment and cloud infrastructure.
* AWS Cloud Practitioner or AWS Architect certification.
* Databricks Certified Data Engineer Associate or Professional certificate a plus.
* Degree/Master’s in Computer Science, Information Technology, Computer Engineering, or equivalent.
* Experience interacting with analytics stakeholders, including clinicians, policy makers, and economists.
* Experience mentoring and providing technical guidance to developers and engineers.
* Familiarity with healthcare informatics and data governance in the healthcare sector.
* Knowledge of cloud security best practices, identity and access management, and data privacy considerations relevant to AI workloads.
* Proficiency in cloud-native architectures and services on both Azure and AWS.
* Project Management Professional (PMP) or similar certification is highly desirable.
* Proven experience with AWS cloud services, including setting up and managing cloud infrastructure, and deep expertise in Databricks Lakehouse and AI/ML technologies.
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