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Data Engineer - Spark (Hybrid/Onsite)

Company:
Cognizant
Location:
North Chicago, IL, 60086
Posted:
May 12, 2025
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Description:

About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all committed, 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 Within AI & Analytics, we work to craft the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.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 informational, relevant intelligence.

Job Summary

We are seeking a Sr. Developer with 8 to 11 years of experience in Spark Optimization Amazon Redshift Big Data AWS EC2 AWS EMR Amazon S3 Apache Spark and Python. The ideal candidate will have a strong background in these technologies and a good understanding of the Manufacturing and Supply Chain domain. This is a hybrid work model with day shifts and no travel required

Responsibilities

Lead the development and optimization of Spark applications to ensure high performance and scalability

Oversee the implementation and management of Amazon Redshift for efficient data warehousing solutions

Provide expertise in Big Data technologies to handle large-scale data processing and analysis

Utilize AWS EC2 to deploy and manage scalable computing resources

Implement and manage AWS EMR for big data processing using Apache Spark

Ensure efficient storage and retrieval of data using Amazon S3

Develop and maintain data processing pipelines using Apache Spark and Python

Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions

Monitor and troubleshoot performance issues in big data applications to ensure optimal functionality

Contribute to the design and architecture of data solutions that support business objectives

Provide technical guidance and mentorship to junior developers

Stay updated with the latest industry trends and technologies to continuously improve the development process

Ensure adherence to best practices and standards in software development and data management

Hands on experience in Informatica Powercenter

Qualifications

Possess strong expertise in Spark Optimization Amazon Redshift Big Data AWS EC2 AWS EMR Amazon S3 Apache Spark and Python

Have a good understanding of the Manufacturing and Supply Chain domain

Demonstrate excellent problem-solving skills and the ability to troubleshoot complex issues

Exhibit strong communication and collaboration skills to work effectively in a hybrid work model

Show a proactive approach to learning and adapting to new technologies

Hold relevant certifications in AWS and Big Data technologies

#LI-NC1

Applications will be accepted until 5/16/2025.

The annual salary for this position is between $110,000 - $125,000 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

Disclaimer: The salary, other compensation, and benefits 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.

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