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Senior Software Engineer - Data Lakehouse Infrastructure

Posted about 9 hours agoViewed

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💎 Seniority level: Senior, 5+ years

💸 Salary: 190000.0 - 220000.0 USD per year

🔍 Industry: Software Development

🗣️ Languages: English

⏳ Experience: 5+ years

Requirements:
  • 5+ years of experience in data or software engineering, with a focus on distributed data systems and cloud-native architectures.
  • Proven experience building and scaling data platforms on GCP, including storage, compute, orchestration, and monitoring.
  • Strong command of one or more query engines such as Trino, Presto, Spark, or Snowflake.
  • Experience with modern table formats like Apache Hudi, Iceberg, or Delta Lake.
  • Exceptional programming skills in Python, as well as adeptness in SQL or SparkSQL.
  • Hands-on experience orchestrating workflows with Airflow and building streaming/batch pipelines using GCP-native services.
Responsibilities:
  • Architect and scale a high-performance data lakehouse on GCP, leveraging technologies like StarRocks, Apache Iceberg, GCS, BigQuery, Dataproc, and Kafka.
  • Design, build, and optimize distributed query engines such as Trino, Spark, or Snowflake to support complex analytical workloads.
  • Implement metadata management in open table formats like Iceberg and data discovery frameworks for governance and observability using Iceberg compatible catalogs.
  • Develop and orchestrate robust ETL/ELT pipelines using Apache Airflow, Spark, and GCP-native tools (e.g., Dataflow, Composer).
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Related Jobs

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🧭 Full-Time

💸 190000.0 - 220000.0 USD per year

🔍 Software Development

  • 5+ years of experience in data or software engineering, with a focus on distributed data systems and cloud-native architectures.
  • Proven experience building and scaling data platforms on GCP, including storage, compute, orchestration, and monitoring.
  • Strong command of one or more query engines such as Trino, Presto, Spark, or Snowflake.
  • Experience with modern table formats like Apache Hudi, Iceberg, or Delta Lake.
  • Exceptional programming skills in Python, as well as adeptness in SQL or SparkSQL.
  • Hands-on experience orchestrating workflows with Airflow and building streaming/batch pipelines using GCP-native services.
  • Architect and scale a high-performance data lakehouse on GCP, leveraging technologies like StarRocks, Apache Iceberg, GCS, BigQuery, Dataproc, and Kafka.
  • Design, build, and optimize distributed query engines such as Trino, Spark, or Snowflake to support complex analytical workloads.
  • Implement metadata management in open table formats like Iceberg and data discovery frameworks for governance and observability using Iceberg compatible catalogs.
  • Develop and orchestrate robust ETL/ELT pipelines using Apache Airflow, Spark, and GCP-native tools (e.g., Dataflow, Composer).
  • Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement
Posted about 2 months ago
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