{"id":2129702,"url":"https://alion.io/job/cognizant-senior-ml-data-infrastructure-engineer","title":"Senior ML Data Infrastructure Engineer","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"B","score":76,"open_postings":86,"ghost_share":0,"stale_share":0.977,"repost_share":0,"time_to_fill_p50_days":24,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":130000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon Kinesis","optional":false},{"name":"Apache Kafka","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"Feast","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"IAM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Rest-Assured","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-08T14:12:56Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-12T22:07:06Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Please note, this role is not able to offer visa transfer or sponsorship now or in the future.\nAbout the role\nAs 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.\nIn this role, you will:\nDesign and implement scalable data processing pipelines for ML training and validation.\nBuild and maintain feature stores with support for both batch and real-time features.\nDevelop data quality monitoring, validation, and testing frameworks.\nCreate systems for dataset versioning, lineage tracking, and reproducibility.\nPartner with data scientists to optimize data preparation workflows.\nWork model\nWe 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.\nThe 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.\nWhat you need to have to be considered\n7+ years of software engineering experience, including 3+ years in data infrastructure.\nStrong expertise in GCP's data and ML infrastructure, including BigQuery, Dataflow, Cloud Storage, Vertex AI Feature Store, Cloud Composer, and Dataproc.\nDeep expertise in data processing frameworks such as Spark, Beam, and Flink.\nExperience with feature stores (Feast, Tecton) and data versioning tools.\nProficiency in Python and SQL, along with experience in data quality and testing frameworks and pipeline orchestration tools such as Airflow or Dagster.\nThese will help you stand out\nExperience with streaming systems (Kafka, Kinesis, or Pub/Sub).\nExperience with GCP-specific security, IAM, and data governance best practices.\nKnowledge of Cloud Logging and Cloud Monitoring for data pipelines, and familiarity with Cloud Build/Cloud Deploy for CI/CD.\nKnowledge of ML metadata management systems.\nExperience with dbt or similar data transformation tools.\nWe'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.\nSalary and Other Compensation\nApplications will be accepted until September 30, 2026.\nThe annual salary for this position is between $130,000- $150,000 depending on experience and other qualifications of the successful candidate.\nThis position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.\nBenefits\nCognizant offers the following benefits for this position, subject to applicable eligibility requirements:\nMedical/Dental/Vision/Life Insurance\nPaid holidays plus Paid Time Off\n401(k) plan and contributions\nLong-term/Short-term Disability\nPaid Parental Leave\nEmployee Stock Purchase Plan\nDisclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. 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