Sr data engg

About the Position

We are seeking a Senior Data Engineer to design scalable data solutions using BigQuery ML and Python, focusing on advanced analytics and machine learning.

Responsibilities

• Design end-to-end cloud data architectures that leverage BigQuery and BigQuery ML to deliver scalable analytics platforms that support complex business reporting and predictive modeling needs for diverse stakeholder groups.
• Develop robust machine learning solutions in BigQuery ML using Python-based feature engineering and model evaluation practices that improve decision quality across critical business processes and external customer services.
• Optimize data warehouse structures and BigQuery query performance by defining partitioning strategies, clustering approaches, and cost control mechanisms that ensure efficient use of resources and rapid insight generation.
• Collaborate with product owners, data scientists, and engineering teams to translate analytical requirements into technical blueprints that integrate BigQuery data assets, Python workflows, and downstream consumption layers.
• Establish standards for data ingestion, transformation, and storage in BigQuery, including reusable patterns for Python-based pipelines to ensure reliability, auditability, and consistent data quality across projects.
• Create architecture documentation and solution diagrams that clearly describe data flows, security controls, and integration touchpoints, enabling teams to implement BigQuery and Python solutions with confidence and alignment.
• Guide teams on best practices for experimenting with BigQuery ML models, including model selection, training, validation, and monitoring to ensure models remain accurate, ethical, and relevant to business objectives.
• Coordinate hybrid work collaboration by defining processes and tools that support effective communication, code review, and design validation for team members working both onsite and remotely in day shift.
• Ensure security and compliance requirements are embedded into all BigQuery and Python solutions by applying encryption, access control policies, and data governance principles that protect sensitive information and build stakeholder trust.

Requirements

• Proficiency in BigQuery and BigQuery ML
• Strong experience with Python
• Ability to develop scalable data architectures
• Experience with machine learning solutions
• Knowledge of data warehousing and optimization techniques

We Offer

• Competitive salary between $100-140K depending on experience and qualifications
• Cognizant’s discretionary annual incentive program
• 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

About the Company

Cognizant (NASDAQ: CTSH) is a builder of AI solutions and a provider of technology services. We bridge the gap between AI investments and enterprise value by building full-stack AI solutions for our clients. Our deep knowledge of sectors, processes, and engineering enables us to anchor the unique context of an organization in technological systems. These systems enhance human potential, deliver tangible results, and give global enterprises an edge in a rapidly changing world. Discover more at cognizant.ai or @cognizant.

Additional Information

The information about the compensation 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 can expect to attend interviews, either in person or via video call. Candidates may also be asked to present a valid, government-issued identification (such as an ID card or passport) during each interview.

Cognizant is an equal opportunity employer. Your application and candidacy will not be judged based on race, color, sex, religion, belief, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status, or any other characteristic protected by federal, state, or local law.