
Chief Data Infrastructure Specialist
18 hours ago
About the Position: We're seeking a seasoned Data Platform Engineer to spearhead data pipeline development and lead cross-functional teams. Key responsibilities include defining technical direction, overseeing design reviews and code reviews, mentoring engineers, and coordinating tasks across geographically dispersed teams.
- Technical Leadership & Delivery: Lead squads or workstreams; scope milestones; manage dependencies and risks; unblock engineers; communicate progress to stakeholders; deliver outcomes on schedule.
- Architecture & Direction: Establish target architectures and data standards; decide build/buy options; author technical specifications; drive cost-effectiveness and reliability patterns.
- Data Pipelines: Design, develop, and operate reliable batch and change-driven pipelines; schedule/orchestrate jobs; handle schema evolution and failures gracefully.
- Transformations & Modeling: Implement clean, tested merge/transformation pipelines; produce models that are easily consumable for products and analytics; optimize SQL for performance.
- APIs & Integration: Develop or collaborate on APIs for data access/updates; design request/response contracts; handle authentication (OAuth2/OIDC/JWT), idempotency, validation, and auditing.
- Infrastructure & DevOps: Provision/manage cloud resources with Terraform; automate build/test/deploy with CI/CD; write solid shell scripts for glue/ops tasks.
- Observability & Reliability: Instrument logs/metrics/traces; define SLOs and on-call runbooks; lead incident reviews and drive root-cause prevention.
- Security & Compliance: Apply least-privilege access, secrets management, and encryption in transit/at rest; partner on compliance requirements.
- Quality & Standards: Champion unit/integration/data-quality tests (including SQL); enforce code health via reviews, linters, and CI checks.
- Collaboration & Docs: Operate asynchronously; produce concise documentation (data contracts, mappings, runbooks, technical specifications); collaborate closely with product/engineering/analytics across time zones.
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