About
We are seeking a highly skilled Data Engineer with strong hands-on experience in BigQuery and Apache Iceberg to design, build, and optimize scalable data platforms.
The ideal candidate will have deep expertise in modern data lakehouse architectures, distributed data processing, and cloud-native data pipelines.
Key Responsibilities: Design, develop, and maintain scalable data pipelines using BigQuery and Iceberg-based data lake architectures Implement and manage Apache Iceberg tables for large-scale, high-performance analytics workloads Build efficient data ingestion, transformation, and storage solutions supporting batch and streaming use cases Optimize query performance, partitioning strategies, and storage formats for cost and performance efficiency Collaborate with data scientists, analysts, and platform teams to deliver high-quality datasets Ensure data quality, governance, and reliability across pipelines and platforms Contribute to architecture decisions for lakehouse and modern data platform design
Required Skills & Qualifications 10+ years of experience in Data Engineering / Data Platform development Strong hands-on expertise in:BigQuery (data modeling, performance tuning, cost optimization)Apache Iceberg (table design, partitioning, schema evolution, time travel) Experience with SQL and distributed data processing frameworks Strong understanding of data lakehouse architectures Experience working with large-scale datasets and cloud-native data platforms Proficiency in Python / Java / Scala
Nice to Have Experience with: Dataflow (Apache Beam) for batch/stream processing Pub/Sub for real-time data ingestion Familiarity with GCP ecosystem (Cloud Storage, Composer, IAM)Exposure to CI/CD, DataOps, and orchestration tools Understanding of data governance and lineage frameworks
Languages
- English
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