Lead a team of data and infrastructure engineers in the overall delivery of data solutions enabling advanced data science and analytics.
Drive the analysis, design, and development of a roadmap and implementation plan to continuously modernize our analytics data and model management platform and improve operational efficiency in accordance with business objectives.
Implement data security measures and ensure compliance with data governance policies and standards.
Engineer secure app patterns into cloud platforms.
Use your knowledge of cloud design patterns, cloud operations, and cloud cost models to identify and address performance bottlenecks, troubleshoot technical issues, and implement optimizations to enhance overall data & model management platform performance.
Work collaboratively with cross-functional teams, including data scientists, analysts, engineers, and business stakeholders, to understand data and ML system requirements and deliver effective solutions.
Be a technology thought leader and a key influencer on technical decisions and organizational strategy that have long-term, strategic impact on the business.
Requirements:
10 or more years of experience (preferred)
Deep knowledge about public cloud architecture, cloud strategy, cloud operations, compliance, and related tools.
Hands-on experience in designing and delivering big data management and applications on cloud platforms using modern software development processes, methodologies, and tools.
Demonstrated experience in working with cloud-based ML frameworks, such as AWS SageMaker AI, Google Vertex AI, Microsoft Azure ML, or Databricks, and in MLOps workflows, patterns and delivery objectives.
Proficient in system design or a programming language such as GoLang, Scala, Python
Demonstrated experience in designing and supporting cloud-based data lakes/warehouses/lakehouses
Excellent collaboration skills and ability to work on a remote team.
Strong analytical, problem solving, and organizational skills.