Snowflake Engagement Lead

Cognizant; Trenton (NJ); On-site; USD 138,000 - 162,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid holidays

Paid Time Off

401(k) plan and contributions

Employee Stock Purchase Plan

Job summary

Cognizant's AI & Analytics practice seeks a Data Architect with deep expertise in Snowflake, AWS, DBT, Python, and modern cloud data platforms to support enterprise data engineering and analytics in the Life Sciences domain.

The role focuses on designing scalable data architectures, building data pipelines, and enabling secure, high-quality data integration across multiple business and operational systems, combining hands-on engineering with architectural leadership to deliver cloud-native data

Qualifications

• 8+ years in Data Architecture, Engineering, Warehousing, or Cloud Data Platforms.
• Hands-on Snowflake, data modeling, security, and administration.
• Extensive experience with AWS services (S3, Glue, Lambda, EMR, Redshift).
• DBT for data transformation, modeling, testing, deployment.
• Python, PySpark, SQL for data processing and automation.
• ETL/ELT design and enterprise data integration knowledge.
• Unix/Linux, shell scripting, and platform administration.
• Data governance, lineage, metadata, and data quality practices.
• CI/CD, Git versioning, DevOps practices.
• Experience in Life Sciences, Healthcare, or regulated industries preferred.

Responsibilities

• Design scalable cloud-native data architectures using Snowflake, AWS, DBT, and Python.
• Develop and maintain enterprise data pipelines for multiple source systems.
• Build and optimize ETL/ELT frameworks to support analytics.
• Design and support Snowflake data warehouses—schema, performance, clustering, cost.
• Utilize AWS services (S3, Glue, Lambda, EMR, Redshift) to support modern data platforms.
• Establish data quality, governance, lineage, and monitoring frameworks.
• Collaborate with stakeholders to translate requirements into scalable solutions.
• Support data migration, modernization, and cloud transformation in Life Sciences.
• Monitor, troubleshoot, and optimize data workflows for reliability.
• Maintain architecture docs, data flow diagrams, and security/compliance standards.

Skills

Snowflake modeling

AWS Cloud

DBT

Python

PySpark

SQL

Unix/Linux

Shell scripting

CI/CD

Git version control

Data governance

Data quality

Data security

Data architecture

Tools

Airflow

Job description

Practice - AIA - Artificial Intelligence and Analytics

About AI & Analytics:

Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human‑centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial‑and‑error business decisions have been replaced by informed choices and data‑supported strategies.

By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery models. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.

Please note, this role is not able to offer visa transfer or sponsorship now or in the future

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.

#LI-EF1

#CB

#Ind123

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:

• 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

Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.