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Cognizant

SR Azure Databricks Engineer

Toronto, ON, Canada

Pay: The annual salary for this position is between $115,000 - $130,000 depending on experience and other qualifications of the successful candidate.
Job type: Full-time
Apply by: Oct 23, 2026
Posting language: English
Posted: Sep 23, 2026

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Original job description

Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.). Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500 and we are among the top performing and fastest growing companies in the world.

Job Title

SR Azure Databricks Engineer

Job Summary

This hybrid role for an experienced data engineer and data architect focuses on designing and optimizing enterprise data platforms using Databricks for a global organization in the life and annuities insurance domain. The candidate will architect scalable data solutions ensure data quality and collaborate with cross functional teams to deliver reliable insights that drive customer value and support critical business decisions while working primarily in a day shift schedule without travel req

Responsibilities

Design and architect scalable data platforms on Databricks to support complex analytical workloads and reporting needs for enterprise insurance data environments
Develop robust data pipelines that ingest transform and curate structured and unstructured data from multiple internal and external sources to create trusted datasets
Optimize Databricks clusters notebooks and workflows to achieve efficient resource utilization cost effectiveness and consistently high performance for batch and near real time processing
Implement comprehensive data quality checks validation rules and monitoring frameworks that ensure accuracy completeness and reliability of life and annuities insurance data assets
Collaborate with data scientists analysts and business stakeholders to translate analytical and reporting use cases into well defined data models and reusable data products
Create detailed logical and physical data models that reflect complex policy customer claims and financial data relationships enabling consistent reporting and downstream analytics
Establish and enforce data governance practices including naming conventions data lineage documentation and access controls to maintain compliance and standardized data usage
Provide clear technical guidance and support to project teams on Databricks best practices coding standards and architectural patterns that improve delivery speed and solution stability
Automate deployment testing and monitoring of data pipelines using modern DevOps approaches to reduce operational risk and shorten time to production for new data features
Analyze system performance logs and data usage patterns to proactively identify bottlenecks and implement tuning strategies that improve query response times and user experience
Document data architectures data flows and transformation logic in an accessible and maintainable manner so that teams across the company can understand and reuse shared assets
Partner with insurance domain experts to align data solutions with life and annuities processes including policy administration underwriting and claims while supporting regulatory reporting
Contribute to the company mission by enabling secure timely and accurate data driven insights that improve customer outcomes product innovation and societal trust in insurance services

Qualifications

Demonstrate substantial hands on experience designing and building data platforms on Databricks including notebooks jobs cluster configuration and integration with cloud storage services
Apply expert level skills in data engineering concepts such as distributed processing data partitioning data modeling and orchestration using tools commonly paired with Databricks
Exhibit solid proficiency in working with large relational and nonrelational datasets and converting complex business rules into efficient transformation logic for analytics consumption
Show proven experience using data engineering practices within large scale enterprises and managing solutions that handle high volume insurance or financial data with strict quality needs
Display strong understanding of life and annuities insurance concepts including policies premiums reserves claims and regulatory constraints to design domain aware data structures
Demonstrate ability to work effectively in a hybrid environment collaborating with onsite and remote stakeholders using clear communication and structured documentation practices
Illustrate experience with modern data governance security and compliance approaches ensuring that sensitive customer and financial data is protected and auditable across the data platform

Certifications Required

Databricks Certified Data Engineer Professional or equivalent advanced data engineering certification

Application Accepted: 9/31/2026

The annual salary for this position is between $115,000 - $130,000 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:

Extended Health Coverage through Manulife
Prescription Drug Coverage
Virtual Care Services (TELUS Health)
Mental Health & Counselling Services
Employee Assistance Program (EAP)
Virtual Pharmacy Services
Retirement Benefits
Registered Pension Plan (RPP) with employer matching up to 3%
RRSP contributions are available; however, Cognizant does not provide RRSP matching

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 language

Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration.

If you are content with ambiguity, excited by change, and excel through autonomy, we’d love to hear from you!

#CB#Ind123

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More about this job

Responsibilities

Design, build, and optimize scalable Databricks data platforms and pipelines for enterprise life and annuities insurance workloads, ensuring data quality, performance, governance, and security. Develop data models and reusable data products, automate deployment and monitoring, document architectures, and collaborate with technical teams and insurance stakeholders to support analytics and regulatory reporting.

Requirements

Requires substantial hands-on experience designing and building Databricks data platforms, strong data engineering expertise, and experience handling large-scale, high-volume datasets in enterprise environments. Candidates should understand life and annuities insurance data and processes, data governance and compliance, and hold the Databricks Certified Data Engineer Professional certification or an equivalent advanced data engineering certification.

Skills

Databricks
Azure
Data Engineering
Data Architecture
Data Pipeline Development
Distributed Processing
Data Modeling
Data Orchestration
Data Quality
Data Governance
Cloud Storage Integration
Cluster Optimization
DevOps
Data Security and Compliance
Life and Annuities Insurance
Performance Tuning

Benefits

Extended Health Coverage
Prescription Drug Coverage
Virtual Care Services
Mental Health and Counselling Services
Employee Assistance Program
Virtual Pharmacy Services
Registered Pension Plan with Employer Matching up to 3%
RRSP Contributions

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Azure
Data Engineering
Data Architecture
Data Pipelines
Distributed Processing
Data Partitioning
Data Modeling
Data Orchestration
Structured Data
Unstructured Data
Cloud Storage
Databricks Notebooks
Databricks Jobs
Cluster Configuration
Data Quality
Data Governance
Data Lineage
Access Controls
DevOps
Automated Testing
Performance Optimization
Life Insurance
Annuities
Policy Administration
Underwriting
Claims
Regulatory Reporting
Databricks Certified Data Engineer Professional

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