Senior ML Data Platform Engineer — Hybrid (SF)

Cognizant; San Francisco (CA); Hybrid; USD 130,000 - 150,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays plus Paid Time Off

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant in San Francisco is seeking a Senior ML Data Infrastructure Engineer to shape the ML data platform, enabling efficient data preparation, feature engineering, and dataset management. You will design scalable pipelines and collaborate with data scientists and platform stakeholders to power ML capabilities.

You will work in a hybrid model, 3-4 days in the SF office, with a strong focus on data quality, reproducibility, and robust feature stores, while navigating evolving requirements and

Qualifications

• 7+ years of software engineering experience, including 3+ years in data infrastructure.
• Strong expertise in GCP's data and ML infrastructure, including BigQuery, Dataflow, Cloud Storage, Vertex AI Feature Store, Cloud Composer, and Dataproc.
• Deep expertise in data processing frameworks such as Spark, Beam, and Flink.
• Experience with feature stores (Feast, Tecton) and data versioning tools.
• Proficiency in Python and SQL, along with experience in data quality and testing frameworks and pipeline orchestration tools such as Airflow or Dagster.

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.
• Partner with data scientists to optimize data preparation workflows.

Skills

Python

SQL

GCP

Data pipelines

Feature stores

Airflow/Dagster

Data quality

Tools

BigQuery

Dataflow

Dataproc

Spark

Beam

Flink

Kafka

Pub/Sub

Job description

Cognizant in San Francisco is seeking a Senior ML Data Infrastructure Engineer to shape the ML data platform, enabling efficient data preparation, feature engineering, and dataset management. You will design scalable pipelines and collaborate with data scientists and platform stakeholders to power ML capabilities.

You will work in a hybrid model, 3-4 days in the SF office, with a strong focus on data quality, reproducibility, and robust feature stores, while navigating evolving requirements and