Technical Program Manager

Role OverviewWe are seeking a Technical Program Manager (TPM) to lead the delivery of our next-generation Data and AI/ML platform. You will bridge the gap between complex data architecture, machine learning engineering, and business strategy.The ideal candidate has a hands-on background as a Data Engineer in their early career and has successfully transitioned into program management. In this role, you will oversee massive data pipelines, migration strategies, and the data infrastructure required to build, train, deploy, and monitor scalable AI/ML and generative AI models on AWS.Core ResponsibilitiesProgram Leadership: Drive end-to-end execution of large-scale AWS data and AI/ML initiatives from roadmap to operational launch.AI/ML Infrastructure Strategy: Oversee the delivery of feature stores, training data pipelines, and MLOps frameworks supporting data science teams.Technical Governance: Review data architectures, ETL/ELT pipelines, and warehouse designs to ensure low latency and high availability for ML model inference.Stakeholder Management: Translate complex data and machine learning blockers into clear, actionable business strategies for executives.Cross-Functional Collaboration: Align data engineers, ML engineers, data scientists, product managers, and security teams.Risk Mitigation: Proactively manage data drift risks, project dependencies, resource bottlenecks, and compliance issues (e.g., data privacy for AI).Agile Orchestration: Lead Scrum-of-Scrums and Agile ceremonies across multiple engineering and data science squads.Required Technical Skills & AWS Ecosystem ExpertiseYou must possess deep familiarity with the following AWS cloud stack and modern data/ML tools:AI/ML & MLOps: Amazon SageMaker (pipelines, feature store, model registry), Amazon Bedrock (for generative AI orchestration), and MLflow.Data Integration: AWS Glue, Amazon EMR, and Apache Airflow for workflow orchestration.Storage & Warehousing: Amazon S3 (Data Lakes/Lakehouses) and Amazon Redshift (Data Warehousing).Streaming & Analytics: Amazon Kinesis, Apache Kafka, or AWS Lambda for real-time streaming data ingestion into ML models.Compute & Databases: Amazon EMR (Spark/Hive), Amazon Athena, OpenSearch Service, and Amazon DynamoDB.Data Ops & Infrastructure: Infrastructure as Code (Terraform), CI/CD pipelines (for both code and models), and dbt (data build tool).Tracking & Governance: Jira, Confluence, and AWS IAM for secure data access management.Qualifications & ExperienceEarly Career Foundations: 3–5 years of hands-on experience as a Data Engineer building production-grade data pipelines.Current Leadership: 3+ years of experience acting as a Technical Program Manager or Project Manager leading data and/or AI/ML initiatives.Cloud Mastery: Proven track record delivering complex data solutions natively built on AWS.Methodology: Deep understanding of Agile, Scrum, or Scaled Agile Framework (SAFe), specifically tailored to iterative data science lifecycles.Education: Bachelor’s degree in Computer Science, Data Engineering, Data Science, or a related technical field.Preferred CertificationsAWS Certified Machine Learning – Specialty or AWS Certified Data Engineer – AssociateProject Management Professional (PMP) or Certified Scrum Product Owner (CSPO) / Scrum Master (CSM)