Snowflake - Team Lead II

• Lead planning and execution across Snowflake, AWS, and AI engineering workstreams, including roadmap alignment, milestone tracking, sprint planning, and delivery forecasting.
• Own delivery governance by maintaining execution plans, RAID logs, action/decision registers, and proactively managing risks, dependencies, and cross-team trade-offs.
• Drive end-to-end SDLC delivery: requirements and design readiness, development oversight, code/design reviews, test strategy, release readiness, production deployments, and hypercare/production support.
• Partner with Data/AI teams to ensure delivery of Snowflake data models/pipelines and AI/ML capabilities (feature pipelines, model integration, evaluation/monitoring) with clear acceptance criteria and measurable outcomes.
• Own stakeholder communication and reporting: weekly status, executive summaries, and KPI dashboards with transparent visibility into progress, blockers, and next steps.
• Drive engineering excellence and compliance by improving velocity/cycle time, defect leakage/DRE, and release stability, while ensuring alignment with security, privacy, and healthcare compliance expectations in partnership with InfoSec/Compliance.

• Bachelor s degree in computer science/engineering (or equivalent practical experience).
• 6+ years of experience in data/software engineering with hands-on expertise delivering solutions on Snowflake and AWS, including scalable data pipelines and platform integration.
• 2+ years of experience as a Tech Lead/Team Lead with proven delivery ownership (planning, design/code reviews, mentoring, and execution management).
• Strong experience building cloud-native services and data products: APIs/microservices, integration patterns, distributed systems (sync/async), and messaging/event-driven architectures.
• Working knowledge of core AWS services (IAM, VPC/networking basics, CloudWatch, S3) plus compute/orchestration such as ECS/EKS/Lambda/EC2; ability to drive security and operational readiness.
• Strong Snowflake experience: schemas/data modeling, ingestion/ELT, performance cost optimization, role-based access, and secure data sharing (as applicable).
• Exposure to AI engineering / ML enablement (e.g., feature pipelines, model integration into services, batch/real-time scoring, model evaluation/monitoring) is preferred.
• Strong CI/CD and engineering practices: Git branching, automated builds/deployments, test automation (unit/integration), and observability.
• Experience in Agile delivery (Scrum/Kanban), including estimation, sprint planning, and release coordination.
• Excellent communication and stakeholder management skills.

• Minimum relevant experience 5+ years
• Preferred total experience 8+ years

• Experience with event streaming and messaging to enable real-time data/AI use cases (e.g., Kafka, AWS SNS/SQS, Kinesis, ActiveMQ).
• Strong familiarity with data engineering on Snowflake/AWS: ETL/ELT, batch vs streaming architectures, data lineage, reconciliation, and data quality controls.
• Exposure to AI engineering / ML operations practices (feature pipelines, model deployment patterns for batch/real-time scoring, monitoring/drift, and governance) is a plus.
• Healthcare domain experience (claims, eligibility, provider/member data) with strong awareness of HIPAA/PHI handling, security, auditability, and compliance expectations.

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