Senior Data Platform Engineer
Summary
Build and optimize scalable data pipelines and platforms using Python, Spark, and GCP, while integrating AI-driven workflows to improve data engineering processes.
Responsibilities
- Design and implement solutions for complex platform challenges, including high‑scale pipeline architecture and modeling decisions
- Conduct technical code reviews focusing on performance, cost, and maintainability
- Act as a technical reference for production troubleshooting and cloud cost optimization
- Collaborate with partner teams on data contracts, latency, quality, and governance
- Identify and lead the execution of addressing technical debt
- Work in an AI‑driven environment to enhance team productivity and data engineering processes
Requirements
- Proficiency in Python, Scala, Java, or Go
- Strong SQL skills
- Knowledge of algorithms, data structures, and application scalability
- Experience with distributed processing frameworks like Apache Spark or Beam
- Containerization and deployment experience with Docker and Kubernetes
- Experience with CI/CD and platform monitoring/observability
- Pipeline orchestration using Airflow, dbt, or Dataform
- Experience with Google Cloud Platform (BigQuery, GCS, GKS, IAM, DataProc, Cloud SQL, Composer, Pub/Sub, Dataflow)
- Management of analytical visualization platforms (Metabase, Looker, Tableau)
Preferred Qualifications
- Experience with AI architectures applied to data (RAG, MCP, agentic systems)
- Construction of data warehouse, data lake, or data lakehouse environments
- Infrastructure as Code (IaC)
Benefits
- Food and/or meal allowance
- Health and dental insurance
- Transportation voucher
- Extended maternity and paternity leave
- Childcare assistance
- Wellhub and Zenklub partnerships
- Education incentives and MBA/Post‑grad partnerships
- Airfare discounts
- Pet health insurance partnership
- Access to Arco educational materials for children of employees