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Urgent! Senior ML Data Infrastructure Engineer Job Opening In Sunnyvale California – Now Hiring Tranzeal Inc.

Senior ML Data Infrastructure Engineer



Job description

Key Responsibilities:


  • Design and implement scalable data processing pipelines for ML training and validation

  • Build and maintain feature stores with support for both batch and real-time features

  • Develop data quality monitoring, validation, and testing frameworks

  • Create systems for dataset versioning, lineage tracking, and reproducibility

  • Implement automated data documentation and discovery tools

  • Design efficient data storage and access patterns for ML workloads

  • Partner with data scientists to optimize data preparation workflows




Technical Requirements:


  • 7+ years of software engineering experience, with 3+ years in data infrastructure

  • Strong expertise in GCP's data and ML infrastructure:

    • BigQuery for data warehousing

    • Dataflow for data processing

    • Cloud Storage for data lakes

    • Vertex AI Feature Store

    • Cloud Composer (managed Airflow)

    • Dataproc for Spark workloads



  • Deep expertise in data processing frameworks (Spark, Beam, Flink)

  • Experience with feature stores (Feast, Tecton) and data versioning tools

  • Proficiency in Python and SQL

  • Experience with data quality and testing frameworks

  • Knowledge of data pipeline orchestration (Airflow, Dagster)


Nice to Have:


  • Experience with streaming systems (Kafka, Kinesis)

  • Experience with GCP-specific security and IAM best practices

  • Knowledge of Cloud Logging and Cloud Monitoring for data pipelines

  • Familiarity with Cloud Build and Cloud Deploy for CI/CD

  • Experience with streaming systems (Pub/Sub, Dataflow)

  • Knowledge of ML metadata management systems

  • Familiarity with data governance and security requirements

  • Experience with dbt or similar data transformation tools






Required Skill Profession

Architecture And Engineering



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