Redolent, Inc

ERM - Rina María Cabrera / Capgemini | North América External Resource Manager Tel.: +1 888 229 2961 Email: rina.cabrera@capgemini.com

ML Data Infrastructure Engineer

Location

United States

Posted

3 days ago

Salary

0

Seniority

Mid Level

No structured requirement data.

Job Description

ML Data Infrastructure Engineer

Redolent, Inc

Role Description - 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 Qualifications - 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) Requirements - 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

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