Job Summary
Sr. Data Engineer role in a global organization focused on designing and optimizing data and analytics platforms using Python Snowflake Cortex and Snowflake SQL within a hybrid work environment. Has handson experiecne in working in GCP Cloud. Role spans end to end solution architecture performance engineering data governance and collaboration with product and business partners to deliver reliable secure and scalable data products that drive measurable business and societal impact.
Responsibilities
Design end to end data platform architectures that leverage Python Snowflake Cortex and Snowflake SQL to deliver secure scalable and maintainable analytics solutions aligned to enterprise standards and long term product vision.Define target state data models and integration patterns in Snowflake that enable efficient analytics reporting and machine learning workloads while optimizing storage query performance and cost.Develop reference implementations and reusable solution patterns using Python and Snowflake features that help engineering teams deliver consistent high quality data products at speed.Collaborate closely with product owners and business stakeholders to translate complex analytical and reporting needs into clear technical architectures and implementation roadmaps.Guide engineering teams on best practices for coding testing deployment and observability of Python based data pipelines and Snowflake workloads to ensure reliability and maintainability.Review solution designs database schemas and query strategies to identify performance bottlenecks and recommend concrete improvements that enhance responsiveness and user experience.Establish governance standards for data quality security access control and lineage within Snowflake to protect sensitive information and support regulatory and compliance expectations.Evaluate new Snowflake Cortex capabilities and related ecosystem tools assess their fitness for purpose and propose pragmatic adoption paths that maximize value for the organization.Create clear technical documentation solution diagrams and implementation guidelines that make it easy for engineering and analytics teams to understand adopt and extend the designed architectures.Partner with enterprise architecture security and infrastructure teams to ensure that data solutions align with broader architectural principles security policies and operational resilience goals.Support incident resolution and root cause analysis for complex data and analytics issues by providing architectural insights technical guidance and actionable recommendations.Mentor engineers and data professionals on modern data architecture concepts Snowflake optimization techniques and Python development standards to uplift overall team capability.Champion responsible and ethical data usage by promoting privacy aware designs and transparent data practices that enhance trust with customers and communities.
Qualifications
Demonstrate ten to fourteen years of experience in designing and implementing data or analytics solutions with a strong focus on building robust and scalable architectures.Show deep hands on proficiency in Python for data processing orchestration and integration including the use of relevant libraries and frameworks for production ready solutions.Exhibit advanced practical experience with Snowflake SQL for data modeling query tuning and implementing complex transformations that meet stringent performance expectations.Possess working experience with Snowflake Cortex capabilities or closely related Snowflake native services used to enable intelligent and automated analytics workflows.Bring solid understanding of data warehousing dimensional modeling and modern data platform concepts including separation of storage and compute workload isolation and cost optimization.Apply strong skills in designing secure data architectures that incorporate role based access encryption practices and governance controls suitable for an enterprise context.Communicate effectively with technical and non technical partners using clear language and structured artifacts to align expectations and enable smooth solution delivery.Work comfortably in a hybrid work model by using collaboration tools documentation and structured communication practices to maintain transparency and productivity across locations.
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.
Language requirements vary depending on roles, but we ask that all candidates have basic English proficiency for company-wide communications purposes. For roles based in Quebec, professional English proficiency is required, as you’ll deliver services to and collaborate with stakeholders outside the province who may not speak French.
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, provincial or local laws.
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