Practice - AIA - Artificial Intelligence and Analytics
Job Summary
We are seeking a Data Architect with strong expertise in Snowflake, AWS, DBT, Python, and modern cloud data platforms to support enterprise data engineering and analytics initiatives within the Life Sciences domain. This role will be responsible for designing scalable data architectures, developing data pipelines, and enabling secure, high-quality data integration across multiple business and operational systems. The ideal candidate will combine hands-on engineering expertise with architectural leadership to deliver modern cloud-native data solutions that support reporting, analytics, and business transformation initiatives.
In this role, you will:
• Design and implement scalable cloud-native data architectures leveraging Snowflake, AWS, DBT, and Python.
• Develop and maintain enterprise data pipelines for ingestion, transformation, validation, and distribution of data from multiple source systems.
• Build and optimize ETL/ELT frameworks using DBT, Snowflake, and cloud-native technologies to support analytics and reporting requirements.
• Design and support Snowflake data warehouse solutions, including schema design, performance optimization, clustering, and cost management.
• Utilize AWS services such as S3, Glue, Lambda, EMR, Redshift, and related services to support modern data platform architectures.
• Establish data quality, governance, lineage, and monitoring frameworks to ensure reliable and trusted data assets.
• Collaborate with business stakeholders, data analysts, and application teams to understand requirements and translate them into scalable technical solutions.
• Support data migration, modernization, and cloud transformation initiatives within Life Sciences environments.
• Monitor, troubleshoot, and optimize data workflows to ensure operational stability, performance, and reliability.
• Maintain architecture documentation, data flow diagrams, solution designs, and operational standards while ensuring compliance with security, regulatory, and governance requirements.
What you need to have to be considered
• 8+ years of experience in Data Architecture, Data Engineering, Data Warehousing, or Cloud Data Platform development.
• Strong hands-on expertise with Snowflake including data modeling, performance optimization, security, and administration.
• Extensive experience with AWS Cloud Services including S3, Glue, Lambda, EMR, Redshift, and cloud-native data architectures.
• Hands-on experience with DBT (Data Build Tool) for data transformation, modeling, testing, and deployment.
• Strong programming skills in Python, PySpark, and SQL for data processing, orchestration, and automation.
• Experience designing and implementing ETL/ELT solutions and enterprise data integration frameworks.
• Strong knowledge of Unix/Linux environments, shell scripting, and platform administration.
• Understanding of data governance, lineage, metadata management, and data quality best practices.
• Experience with CI/CD pipelines, Git-based version control, and modern DevOps practices.
• Experience within Life Sciences, Pharmaceutical, Healthcare, or regulated industries is highly preferred.
• Excellent communication, stakeholder management, problem-solving, and technical leadership skills.
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Applications will be accepted until 8 Sep 2026.
Salary and Other Compensation:
The annual salary for this position is between $[137,500 - 161,500] 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:
• 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
