Senior Data Platform Architect
Indexed description
Our mission is to build the digital infrastructure for the global experience economy — empowering merchants to share their passions and travelers to discover the heartbeat of each destination.
We operate a mobile-first, curated platform featuring diverse experiences across global destinations.
Do you share our belief in the wonders of travel? Global citizens ourselves, Klookers are not only curating memorable experiences for others but co-creating our world of joy within Klook.
We work hard and play hard, upkeeping our high-performing culture as we are guided daily by our 6 core values:
- Customer First
- Push Boundaries
- Critical Thinking
- Build for Scale
- Less is More
- Win as One
Role Overview
We are seeking a seasoned Data Platform Architect with deep expertise in modern data technologies (e.g., Flink, Kafka, Lakehouse, Paimon, Doris, BigQuery) and Google Cloud Platform (GCP). You will design, build, and optimize scalable data platforms, ensuring seamless integration with data ingestion, warehousing, AI/ML pipelines (Vertex AI), and data governance (Data Catalog). The ideal candidate is a hands-on leader who can bridge technical execution with strategic vision.
What You'll Do
Architect Modern Data Platforms:
- Design and implement scalable, real-time data solutions using Apache Flink, Kafka, Lakehouse architectures, Apache Paimon, Apache Doris, and BigQuery.
- Optimize data pipelines for batch/streaming workflows, ensuring low-latency and high throughput.
- Lead GCP-based data ingestion (Pub/Sub, Dataflow), warehousing (BigQuery, Dataproc), and ML pipelines (Vertex AI, TFX).
- Implement DataOps/MLOps practices for CI/CD, monitoring, and governance.
- Deploy and manage data catalogs (e.g., Data Catalog, Collibra, Alation) for metadata management, lineage, and compliance.
- Enforce data quality, security, and access controls.
- Collaborate with AI/ML teams to productionize models and embed analytics into business processes.
- Mentor engineers and evangelize best practices in cloud-native data architectures.
- 8+ years in data engineering, architecture, or solutions roles, with at least 3 years focused on GCP.
- Proficiency in real-time data tools: Flink, Kafka, Paimon, Doris, Spark.
- Hands-on experience with GCP services: BigQuery, Dataflow, Pub/Sub, Dataproc, Vertex AI, Cloud Storage.
- Strong SQL/Python/Java/Scala skills; familiarity with data lakehouse frameworks (Delta Lake, Iceberg, Hudi).
- Experience with data catalogs (e.g., GCP Data Catalog, OpenMetadata) and metadata management.
- Proven track record designing large-scale data platforms (10M+ rows/day).
- Ability to translate business needs into technical solutions.
- Certifications like GCP Professional Data Engineer or AWS/Azure equivalents are a plus.
- Knowledge of multi-cloud integrations (e.g., AWS S3 + GCP).
- Exposure to LLM pipelines, vector databases, or generative AI workflows.
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