Data Engineer – AWS PySpark | Cognizant India Jobs – Remote Opportunities

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Overview

Hello Readers Cognizant have another Data Engineer job in India if you are looking for Remote Data Engineer jobs India or looking for Data Engineer job with AWS Big Data skills then this post will be the game changer for you lets have a look what the cognizant for you in details

Cognizant is looking for a talented Data Engineer skilled in AWS and PySpark to join our dynamic team. In this role, you will work closely with cross-functional teams to implement data solutions that drive our operations forward. This opportunity is ideal for analytical thinkers who thrive in collaborative environments and are passionate about harnessing the power of Big Data and Cloud Technology to solve complex problems.

If you’re someone who loves delving into data and developing code for real-world applications, this role could be your perfect fit.

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Job Post

Location: India (Remote)

Job Role: AWS PySpark Data Engineer role

Employment Type: Full-time

Company: Cognizant

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Key Responsibilities

• Project Planning & Setup: Collaborate with project leads to understand the scope, set task estimates, and identify dependencies and risks. Provide insights into configuration, deployment, and hardware/software requirements.
• Requirement Analysis: Analyze both functional and non-functional requirements and suggest feasible technical solutions. Provide feedback on upstream and downstream systems to ensure a cohesive workflow.
• Design & Coding:
• Prepare detailed design documents and develop code adhering to best practices.
• Lead the creation of module-specific designs and components inventory, aligning with project objectives.
• Identify data patterns and use cases to select optimal tools and technologies for code customization.
• Testing & Quality Assurance: Develop and conduct unit and integration testing, addressing any quality gaps. Guide team members in unit testing and ensure quality compliance across testing stages.
• Configuration & Deployment: Track code versions, assist administrators in configuration, and ensure smooth deployment. Conduct post-deployment sanity checks and provide regular activity updates.
• Service Support & Maintenance: Provide initial support post-deployment, assist in transitioning to the production team, and document knowledge for future reference.

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Qualifications

• Education: Bachelor’s degree in Science, Engineering, or a related field.
• Must-Have Skills:
• AWS Big Data experience
• Strong understanding of AWS Services and their integration with Big Data
• Good-to-Have Skills:
• Experience with AWS Cloud technologies
• Proficiency in PySpark and Python
• Additional Skills:
• Analytical and problem-solving skills
• Ability to conduct technical troubleshooting and perform root cause analysis
• Experience with code version management and configuration

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Skills Required

• AWS Big Data: Proficient in AWS Big Data tools and strategies to efficiently handle large datasets.
• AWS Services: Deep understanding of services within AWS, including data storage and management solutions.
• PySpark & Python: Coding experience with PySpark and Python, essential for data manipulation and transformation tasks.
• Data Analysis: Ability to analyze data, recognize patterns, and optimize data flows.
• Project Management: Experience in managing project phases from planning and design to deployment and troubleshooting.

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Roles & Responsibilities

• End-to-End Data Solutions: Work on data engineering solutions that enable the integration and processing of big data.
• Code Quality and Testing: Ensure high standards of code quality and coordinate testing efforts to validate solutions.
• Cross-functional Collaboration: Engage with project leads and developers to synchronize tasks and enhance productivity.
• Documentation & Knowledge Sharing: Contribute to knowledge management by documenting lessons learned, best practices, and creating training resources.
• Guidance and Troubleshooting: Guide team members through technical challenges and resolve critical issues impacting data operations.

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Job Description

As a Data Engineer at Cognizant, you will play a key role in designing, developing, and implementing scalable data engineering solutions. This role demands expertise in AWS Big Data and PySpark, enabling you to build high-quality, production-grade data applications.

You will be responsible for analyzing requirements, preparing technical documentation, and collaborating with data analysts and developers to create innovative solutions. The position involves both independent work and team collaboration, requiring you to balance task management and proactive issue resolution. As part of your daily responsibilities, you’ll be coding, troubleshooting, and optimizing workflows to ensure that our data operations are seamless and efficient.

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Interview Preparation Tips

1. Brush Up on AWS Services: Familiarize yourself with core AWS services and big data processing frameworks to discuss their applications in data engineering.
2. Showcase Your PySpark Skills: Be prepared to demonstrate your PySpark coding proficiency with examples of previous work.
3. Understand Data Patterns: Highlight your ability to recognize patterns and insights within large datasets, an essential skill for this role.
4. Problem-Solving Approach: Cognizant values a structured problem-solving approach. Practice explaining how you troubleshoot data issues or technical challenges.
5. Stay Updated on Industry Trends: Familiarize yourself with current trends in big data, cloud computing, and data engineering methodologies to show your industry awareness.

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Study Materials & Resources

• AWS Big Data Specialization (AWS Training and Certification)
• PySpark and Python for Data Engineering (DataCamp and Coursera)
• Hands-On Data Analysis with PySpark by Rudy Lai (Book)
• Cognizant Blog: Follow Cognizant’s blog for insights on big data and cloud technology advancements.

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Technical Interview Questions & Answers

Technical Questions

1. What are the core services provided by AWS for Big Data?

• Answer: Core AWS services include Amazon S3, Redshift, EMR, and Glue, which facilitate data storage, processing, and analysis.

1. Explain the difference between Spark and PySpark.

• Answer: Spark is a general-purpose cluster-computing system, while PySpark is its Python API, enabling data scientists to process large datasets using Python.

1. How would you troubleshoot a slow-running PySpark job?

• Answer: I would start by analyzing the job’s data shuffling, memory utilization, and potential bottlenecks in transformation stages to optimize performance.

Non-Technical Questions

1. How do you handle tight deadlines while ensuring data quality?

• Answer: I prioritize tasks, use automated tools for validation, and regularly update stakeholders to balance timelines and quality.

1. Describe a time you had to collaborate remotely on a challenging project.

• Answer: I used tools like Slack and Jira to maintain communication and set regular check-ins to ensure project goals were met efficiently.

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Salary & Benefits

• Competitive Salary: Based on experience and skills.
• Work from Home: Enjoy a fully remote role with a flexible work environment.
• Professional Development: Opportunities to grow and enhance your skills with ongoing learning resources.
• Collaborative Culture: Join an energetic and inclusive workplace that encourages innovation.

Cognizant Recruitment Drive Application Process:-

Apply In Below Link

Apply Link:- Click Here To Apply (Apply before the link expires)

Application Process

• Step 1: Submit an application on the Cognizant Careers portal.
• Step 2: Participate in an initial screening call.
• Step 3: Complete a technical assessment focusing on AWS and PySpark.
• Step 4: Attend a final interview round.

Apply now and kick-start your career with Cognizant as a Data Engineer. This opportunity is ideal for professionals looking to leverage their AWS and PySpark skills in a dynamic, growth-oriented environment.

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FAQs – Data Engineer (AWS PySpark) at Cognizant

1. What qualifications are required for the Data Engineer position at Cognizant?

• Answer: Candidates should have a bachelor’s degree in Science, Engineering, or a related field, along with expertise in AWS Big Data, PySpark, and familiarity with AWS Cloud technologies and Python.

2. What is the primary role of a Data Engineer at Cognizant?

• Answer: The Data Engineer is responsible for planning, designing, and implementing data engineering solutions using AWS services and PySpark. This includes coding, testing, deployment, and providing support for data-driven projects.

3. Does this role require prior experience with AWS services?

• Answer: Yes, hands-on experience with AWS Big Data tools and services, along with PySpark, is essential for this position.

4. Is this Data Engineer position at Cognizant a remote opportunity?

• Answer: Yes, this role is remote-friendly, allowing candidates from across India to apply and work from their preferred location.

5. What skills are most important for success in this role?

• Answer: Key skills include AWS Big Data expertise, PySpark, Python programming, analytical and problem-solving abilities, and experience in managing data engineering projects from end to end.

6. How can I prepare for the technical interview for the Data Engineer role?

• Answer: Candidates should review AWS and PySpark fundamentals, practice coding in Python, and be prepared to discuss data engineering principles and real-world applications of big data solutions.

7. What can I expect in terms of career growth at Cognizant as a Data Engineer?

• Answer: Cognizant provides opportunities for continuous learning and development. Data Engineers can grow by taking on more complex projects, gaining exposure to advanced data technologies, and collaborating with skilled teams globally.

8. What makes Cognizant a good choice for data engineering professionals?

• Answer: Cognizant offers a collaborative, innovative, and inclusive work environment, along with competitive benefits and professional growth opportunities. It’s a place where data engineers can make a tangible impact on large-scale data projects.

9. How does Cognizant support work-life balance for its employees?

• Answer: Cognizant values its employees’ well-being, offering remote work flexibility, supportive management, and a culture that encourages maintaining a healthy work-life balance.

10. How can I apply for the Data Engineer – AWS PySpark position at Cognizant?

• Answer: Interested candidates can apply through the official Cognizant Careers portal. The application process includes submitting a resume, completing a technical assessment, and attending an interview.