Lead Data Platform Architect

We are seeking an experienced Senior Data Engineer to join our team. The successful candidate will be responsible for designing, building, and operating large-scale data pipelines, as well as leading a small squad or workstream.

• 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.

• 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 Claude Code (and similar assistants) to accelerate work—while exercising judgment and writing your own code/tests.

• 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.

• Resume/CV highlighting data engineering, DevOps/IaC, and/or API/auth work.
• Brief note (one paragraph) about a recent pipeline/service: requirements, your role, tech, validation/tests, deployment/ops, outcome.
• Links to code samples or design docs (if available/shareable).