Senior Developer – Databricks (Data Engineering) About Cognizant
Cognizant (NASDAQ: CTSH) is a leading professional services company, helping organizations modernize technology, reimagine processes, and transform experiences in a fast-changing world. We combine deep industry expertise with a global delivery model to drive measurable business outcomes.
We are committed to fostering an inclusive, collaborative workplace where innovation thrives and employees can grow and succeed. About the Role
We are seeking a highly experienced Senior Developer – Databricks to design and build scalable, cloud-based analytics platforms. This role requires deep hands-on expertise in Databricks SQL, PySpark, and Databricks Workflows , with a strong focus on enabling enterprise-scale data solutions.
You will collaborate closely with business and technology stakeholders to translate complex requirements into robust data architectures. Experience in the Life & Annuities insurance domain is a strong asset. Key Responsibilities
Design and evolve end-to-end data architecture on Databricks to support scalable analytics and reporting
Develop and optimize PySpark-based pipelines for large-scale data processing (structured and semi-structured)
Build high-performance Databricks SQL models, queries, and semantic layers for reporting and analytics
Define and implement Databricks Workflows orchestration standards , including scheduling, dependency management, and monitoring
Translate business needs into scalable, reliable data solutions
Establish best practices for coding, testing, performance tuning, and monitoring
Implement enterprise data governance standards (lineage, access controls, naming conventions)
Ensure architectures align with security, cost efficiency, and cloud best practices
Collaborate with data modelers to define logical and physical data models
Partner with platform and security teams to ensure policy compliance
Drive continuous improvement through performance analysis and optimization
Contribute reusable frameworks and accelerators
Communicate technical decisions and trade-offs to diverse stakeholders Required Qualifications
6+ years of experience in data engineering or cloud-based analytics
Strong hands-on expertise in:
Databricks SQL
PySpark
Databricks Workflows
Experience building scalable, high-performance data pipelines
Strong knowledge of distributed data processing and data warehousing
Experience with data governance, quality, and security frameworks
Excellent communication and stakeholder engagement skills
Bachelor’s degree in a relevant field or equivalent experience Preferred Qualifications
Experience in Life & Annuities insurance
Experience with Azure data ecosystem or similar cloud platforms
Strong understanding of data modeling and semantic layers
Certifications such as:
Databricks Certified Data Engineer Professional
Azure Data Engineer Associate
Equivalent cloud/data certifications Work Environment
Location: Toronto, Ontario, Canada
Work Model: Hybrid (combination of in-office and remote work)
Shift: Day shift with collaboration across distributed teams Salary & Benefits (Canada)
Base Salary Range: CAD $95,000 – $120,000 per year
(Actual compensation will be determined based on experience, skills, and location.)
Benefits include:
Comprehensive health and dental coverage
Life and disability insurance
Retirement savings plans (RRSP with company contributions where applicable)
Paid time off, including vacation and statutory holidays
Employee wellness programs and mental health support
Opportunities for learning, certification, and career advancement
Flexible work arrangements to support work-life balance Why Cognizant
Work on cutting-edge data and analytics platforms
Opportunity to influence enterprise-scale transformation initiatives
Collaborative and inclusive work culture
Continuous learning and professional growth opportunities Equal Opportunity Statement
Cognizant is an equal opportunity employer. We are committed to creating a diverse and inclusive environment and encourage applications from all qualified candidates.
