Job description

Please note, this role is not able to offer visa transfer or sponsorship now or in the future. About the role As a Senior ML Data Infrastructure Engineer, you will make an impact by building the ML data infrastructure platform that enables efficient data preparation, feature engineering, and dataset management for machine learning. You will focus on the data foundation that powers our ML capabilities. You will be a valued member of the ML Platform Engineering team and work collaboratively with data scientists and platform stakeholders. In this role, you will: • 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. Work model We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 3-4 days a week in a client or Cognizant office in San Francisco, California. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs. The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations. What you need to have to be considered • 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. These will help you stand out • Experience with streaming systems (Kafka, Kinesis, or Pub/Sub). • Experience with GCP-specific security, IAM, and data governance best practices. • Knowledge of Cloud Logging and Cloud Monitoring for data pipelines, and familiarity with Cloud Build/Cloud Deploy for CI/CD. • Knowledge of ML metadata management systems. • Experience with dbt or similar data transformation tools. We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role. Salary and Other Compensation Applications will be accepted until September 30, 2026. The annual salary for this position is between $130,000- $150,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans. Benefits Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: • 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 Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law. About Cognizant: Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant. Additional employment information Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law. Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview. Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws. If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com for roles based in the Americas or CareersIndia2@cognizant.com for roles based in India.

Requirements

Must-haves

Please note, this role is not able to offer visa transfer or sponsorship now or in the future.
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.
What you need to have to be considered
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.
These will help you stand out
Experience with streaming systems (Kafka, Kinesis, or Pub/Sub).
Experience with GCP-specific security, IAM, and data governance best practices.
Knowledge of Cloud Logging and Cloud Monitoring for data pipelines, and familiarity with Cloud Build/Cloud Deploy for CI/CD.
Knowledge of ML metadata management systems.
Experience with dbt or similar data transformation tools.
Salary and Other Compensation
Applications will be accepted until September 30, 2026.
The annual salary for this position is between $130,000- $150,000 depending on experience and other qualifications of the successful candidate.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningrestgcpaipythonsqlci/cd

Platform: cognizant
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave