6 дней назад
Data Platform Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Platform Engineer (AI): Building and operating ingestion pipelines, orchestration workflows, governance, and self-serve tooling for a Databricks lakehouse with an accent on data integrity, reliability, security, and cost efficiency. Focus on handling schema evolution and CDC, hardening CI/CD, tuning Spark and Databricks workloads, and tracing data-quality issues to root cause.
Location: Sydney, New South Wales, Australia; hybrid workplace
Company
is a food technology scaleup that helps restaurants and bars fill tables, increase foot traffic, and grow revenue through a platform serving millions of customers and thousands of venues.
What you will do
- Build and operate ingestion pipelines for source integrations, CDC feeds, and third-party APIs, including schema evolution, backfills, and replay.
- Own orchestration workflows, scheduling, dependencies, retries, alerting, and dataset SLAs.
- Harden CI/CD with trunk-based development, pull-request checks, automated tests, and controlled environment promotion.
- Govern the data platform through access grants, lineage, tagging, row- and column-level security, and safe external data sharing.
- Manage platform cost and performance through warehouse and cluster sizing, partitioning, clustering, and incremental processing.
- Build data quality, observability, and self-service tooling for analysts and data scientists.
Requirements
- Strong SQL and Python skills for commercial-scale products.
- Hands-on experience building and operating production data pipelines on a cloud data platform.
- Experience with orchestration and scheduling tools such as Databricks Workflows, Airflow, or Dagster.
- Experience integrating internal APIs and third-party tools while maintaining data integrity.
- Strong software engineering practices, including Git, CI/CD, trunk-based development, and testing.
- Familiarity with AI-first development, Claude Code, agentic workflows, and daily AI-assisted delivery.
Nice to have
- Experience with Databricks and dbt Core.
- Familiarity with AWS.
- Experience tuning Spark or Databricks workloads, including partitioning, liquid clustering, and warehouse sizing.
- Streaming or CDC experience with Structured Streaming, Debezium, or Delta Live Tables.
- Experience applying AI and LLMs to practical business problems.
Culture & Benefits
- AI-first culture with Claude Code, agentic workflows, and human final review.
- High ownership in a small team building the data platform foundations.
- Fast delivery cycles with frequent feedback from production pipelines and dashboards.
- Staff discounts and dining vouchers.
- Fast-paced environment with changing priorities and end-to-end ownership.
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