
Chief Data Architecture Specialist
2 days ago
We're seeking a highly skilled and experienced Lead Data Platform Engineer to join our team. As a key member of our engineering organization, you will play a crucial role in designing, building, and operating production-grade data pipelines.
The ideal candidate will have a strong background in data engineering, DevOps, and API design, with experience leading engineers or owning large-scale projects. You should be comfortable running design reviews, giving actionable feedback, and collaborating closely with product, engineering, and analytics teams.
Key Responsibilities:
- Technical Leadership & Delivery: Lead a small squad or workstream; scope milestones; manage dependencies and risks; unblock engineers; communicate status to stakeholders; land outcomes on time.
- Architecture & Direction: Define target states and data contracts; make build/buy calls; author RFCs; drive cost/performance guardrails and reliability patterns.
- Data Pipelines: Design, build, 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 easy to consume for products and analytics; tune SQL for performance.
- APIs & Integration: Build or collaborate on APIs for data access/updates; design request/response contracts; handle auth (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 async-first; produce concise docs (data contracts, mappings, runbooks, RFCs); collaborate closely with product/engineering/analytics across time zones.
Required Skills & Qualifications:
- Proven leadership: led engineers or owned large, multi-team projects; comfortable running design reviews and giving actionable feedback.
- Strong SQL (tuning, indexing, query plans) and solid RDBMS fundamentals (e.g., Postgres, SQL Server, MySQL).
- Python for data work and services; comfortable with shell scripting (bash preferred; Powershell acceptable).
- Terraform and IaC fundamentals; CI/CD experience (version control workflows, automated tests, environment promotion).
- Cloud: Azure preferred (storage, compute, identity, monitoring). If not Azure, very strong AWS background.
- Data integration: Ingestion (batch + change-driven), orchestration, schema/versioning, resilient retries/replays.
- Workflow orchestration: Prefect preferred (flows/deployments, retries/backoff, scheduling, observability); Airflow/Dagster also acceptable.
- APIs & auth: REST patterns, pagination, validation, rate limiting, OAuth2/OIDC/JWT.
- Observability: Logs/metrics/traces and actionable alerts/dashboards.
- Testing mindset: Habit of writing tests for code and SQL; fixtures/test data; CI.
- Communication: Clear written/verbal comms; practiced cross-timezone collaboration.
- AI tooling: Ready to use AI tools to accelerate work—while exercising judgment and writing your own code/tests.
Benefits:
- Duration: 10+ months (extension/full-time possible).
- Schedule: Flexible, with overlap for key meetings across time zones.
- Mode: Remote; available for virtual collaboration and on-call windows as agreed.
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