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Senior role with metro location and a common Engineering Manager title increases applicant density moderately.
Strong domain-specific data, cloud, and consulting delivery experience makes cross-industry transferability limited.
Explicit 8+ years requirement, 3+ years management, and mandatory deep data/cloud/ML skills raise strictness.
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Lead delivery quality, engineering health, and people growth for 15–25 engineers across 2–4 concurrent client engagements in cloud, data, and AI/ML practices.
Own end-to-end SOW-to-go-live execution including scoping, milestone planning, risk management, and stakeholder communication with client engineering leadership.
Provide hands-on technical leadership by reviewing PRs, participating in architecture reviews, resolving escalations, and coaching senior engineers through technical decisions.
8+ years building and operating production software, with at least 3 years in engineering management.
Hands-on technical expertise in at least two of: Google Cloud Platform (BigQuery, Cloud Run, GKE/Kubernetes, Vertex AI), Looker/LookML, Elasticsearch/OpenSearch, modern data engineering tools, or production AI/ML systems.
Experience with container and deployment patterns on GCP (Kubernetes, Cloud Run, serverless) and judgment to guide team choices.
Work Experience Required: Minimum 8 years total, 3 years managing engineers (mix of IC and management) explicitly stated.
Strategic leader comfortable managing senior engineers and technical leads across multiple projects simultaneously in a consulting environment.
Expertise in cloud modernization, data platforms, AI/ML, and observability technologies with experience shipping client engagements end-to-end.
Proven ability to handle ambiguity, replan frequently, and communicate clearly with both technical teams and client leadership.