Senior Data Engineering Leadership Position

**Senior Data Engineering Leadership Role**

This position requires a highly skilled engineer to lead the development and operation of production-grade data pipelines.

The successful candidate will be responsible for providing technical direction, designing and building reliable batch and change-driven pipelines, and handling schema evolution and failures gracefully.

• Main Responsibilities:
• Lead the development of data platform projects, including defining technical direction and coaching engineers.
• Design, build, and operate reliable batch and change-driven pipelines, schedule/orchestrate jobs, handle schema evolution and failures gracefully.
• Implement clean, tested merge/transformation pipelines, produce models that are easy to consume for products and analytics, tune SQL for performance.
• Build or collaborate on APIs for data access/updates, design request/response contracts, handle auth (OAuth2/OIDC/JWT), idempotency, validation, and auditing.
• Provision/manage cloud resources with Terraform, automate build/test/deploy with CI/CD, write solid shell scripts for glue/ops tasks.
• Instrument logs/metrics/traces, define SLOs and on-call runbooks, lead incident reviews and drive root-cause prevention.
• Apply least-privilege access, secrets management, and encryption in transit/at rest, partner on compliance requirements.
• Champion unit/integration/data-quality tests (including SQL), enforce code health via reviews, linters, and CI checks.
• Closely collaborate with product/engineering/analytics across time zones, operate async-first, produce concise docs (data contracts, mappings, runbooks, RFCs).

**Key Skills & Qualifications:**

• 9+ years of experience in Data Engineering / Backend Engineering / DevOps, including leadership of a team (or end-to-end ownership of large, multi-stakeholder projects).
• 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.

**Desirable Skills & Experience:**

• Experience mentoring, interviewing, onboarding, and raising code quality standards.
• Regulatory/compliance awareness (e.g., data protection or public-sector standards) and how it impacts design/operations.
• Analytics exposure (dim/fact modeling, BI consumption patterns).
• Data platform architecture exposure (storage/layout choices, catalog/lineage, governance concepts).
• Familiarity with Kafka, streaming/message queues, and columnar formats (e.g., Parquet).
• Experience with cloud monitoring stacks (Azure Monitor/Application Insights, CloudWatch, Datadog, New Relic, etc.).

**Why This Role?**

This is an exciting opportunity to take on a senior leadership role in data engineering. The ideal candidate will have a proven track record of delivering complex data projects and leading teams.