Vetted Scala Professionals

“Amazon engineering leader (15+ years) targeting Senior Manager/Director roles, with deep ownership of contact-center latency and reliability initiatives. Shipped a global production improvement cutting call latency 30–40% and led a complex Citrix SDK integration, including incident response and a backward-compatible rollout strategy to protect existing customers while enabling new features.”

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

“Engineering leader who built and scaled a distributed team (Serbia + US) to deliver an internal multi-tenant Kubernetes-based PaaS, moving a large org from manual ops-driven deployments to automated CI/CD with >99.97% uptime and 100% service adoption. Known for culture change (blameless post-mortems, clear intake via ticketing) and security-first platform practices (tenant isolation, Falco) supporting SOC2 compliance; also operates at exec level with stakeholder communication and fundraising.”

“Fitbit engineer who has taken multiple projects from concept to release, including architecting a new warranty-evaluation system that achieved 100% accuracy and saved the company $6M. Interested in exploring startup ideas and emphasizes mission alignment and building strong cross-functional teams.”

“Data engineer focused on building and operating reliable Airflow-orchestrated pipelines into BigQuery, including daily billing ingestion (~1GB/day) and ad platform (Facebook/LinkedIn) data collection. Implemented end-to-end data quality checks plus org-wide incident response automation integrating PagerDuty, Slack, and Jira, and has experience executing large backfills (4–5TB) via time-window batching.”