Senior AWS Data Engineer — PySpark/Databricks + Snowflake

Cognizant; Missouri; Hybrid; USD 100,000 - 120,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid holidays

Paid Time Off

401(k) plan

Disability Insurance

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking an AWS Data Engineer to design and deliver scalable data platforms for healthcare analytics. You will lead PySpark/Python solutions on AWS, optimize Databricks notebooks and build robust Snowflake data models.

The role requires 9–12 years in data and cloud projects with strong governance and collaboration across teams. The position offers a hybrid work model with onsite and remote collaboration, and requires certifications like AWS Data Analytics Specialty.

Qualifications

• Nine to twelve years of experience in data and cloud projects.
• Experience with PySpark and Python to design scalable data pipelines.
• Proficient in AWS services to build secure, scalable data platforms.
• Databricks expertise for shared workspaces and cluster configs.
• Snowflake skills for tuning queries and managing warehouses.
• Payer domain knowledge in health care analytics preferred.

Responsibilities

• Lead complex data engineering initiatives using PySpark and Python to design and optimize resilient data pipelines for analytics.
• Oversee end-to-end AWS cloud data solutions and ensure architectural alignment with enterprise standards.
• Provide guidance on Databricks usage to standardize notebooks, jobs, and clusters.
• Drive Snowflake data models for analytics stakeholders and ensure scalable query performance.
• Coordinate migration of legacy data processes to modern lakehouse architectures and ensure security/compliance.
• Execute data quality checks and validation routines to ensure trustworthy outputs.
• Translate payer domain requirements into robust data transformations for health outcomes and cost management.
• Collaborate with product analytics and operations to prioritize backlog and deliver value.
• Optimize scheduling and resource use across PySpark, Databricks, and Snowflake environments.
• Implement secure data access practices on AWS and Snowflake with proper roles and encryption.
• Document architectures and operational procedures for cross-functional teams.
• Support incident analysis and root cause resolution for data pipelines.
• Coordinate hybrid work cadence for onsite/remote collaboration.

Skills

PySpark

Python

AWS

Databricks

Snowflake

Data pipelines

Cloud architecture

Tools

AWS services

Databricks

Snowflake

PySpark

Python

Job description

Cognizant is seeking an AWS Data Engineer to design and deliver scalable data platforms for healthcare analytics. You will lead PySpark/Python solutions on AWS, optimize Databricks notebooks and build robust Snowflake data models.

The role requires 9–12 years in data and cloud projects with strong governance and collaboration across teams. The position offers a hybrid work model with onsite and remote collaboration, and requires certifications like AWS Data Analytics Specialty.