
Data Platform Engineer
2 days ago
Engagement Type: Contract
Language: Proficient English communication
Experience: 4+ years in Data Engineering / Backend Engineering / DevOps
We're looking for a hands-on Data Platform Engineer to build and operate production-grade data pipelines and services. You'll work across ingestion, transformation, orchestration, and APIs; Azure experience is preferred; strong AWS experience is also acceptable. You should communicate clearly (async chat and live sessions), learn fast, and use AI coding tools (e.g., Data pipelines : Transformations & modeling : Implement clean, tested merge and transformation pipelines and produce models that are easy to consume for products and analytics; tune SQL for performance.
Build or collaborate on APIs for data access and updates; Infrastructure & DevOps : Provision and manage cloud resources with Terraform; automate build/test/deploy with CI/CD; define alert policies and on-call runbooks; Quality & tests : Write unit, integration, and data-quality tests (including SQL tests) to keep pipelines and services correct and maintainable.
Communicate clearly in writing and in person; produce concise docs (data contracts, mappings, runbooks); Strong SQL (query tuning, indexing, query plans) and solid RDBMS fundamentals (e.g., Postgres, SQL Server, MySQL).
Python for data work and services; CI/CD experience (version control workflows, automated tests, environment promotion).
Cloud : storage, compute, identity, monitoring). If not Azure, very strong AWS background.
Data integration : Experience with ingestion (batch + change-driven), orchestration, schema/versioning, and resilient retries/replays.
Prefect preferred (flows/deployments, retries/backoff, scheduling, observability); Practical experience with REST patterns, pagination, validation, rate limiting, and OAuth2/OIDC/JWT.
Testing mindset : Habit of writing tests for code and SQL; comfortable with fixtures/test data and CI.
Clear, concise writing and verbal comms; comfortable in async chat and live sessions.
AI tooling : Ready to use Claude Code (and similar assistants) from day one to accelerate work—while exercising judgment and writing your own code/tests.
Regulatory/compliance awareness (e.g., data protection or public-sector standards) and how it impacts design/operations.
Analytics experience (dim/fact modeling, BI consumption patterns).
Full-stack exposure (can prototype simple UI/ops views when needed).
Data platform architecture exposure (storage/layout choices, catalog/lineage, governance concepts).
Experience with cloud monitoring stacks (Azure Monitor/Application Insights, CloudWatch, Datadog, New Relic, etc.).
Duration : 6+ months (extension/full-time possible)
Flexible, with overlap for key meetings across time zones
Compensation : Competitive, based on experience
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
Apply via LinkedIn or by sending an email to
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