LAM-MTS, AWS, PySpark

EXL

Data Engineer specializing in PySpark, Python, SQL, and AWS services to develop robust data infrastructure. Collaborate with teams to transform and optimize data processes.

Posted 7/20/2026full-timeNoida • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining ETL pipelines using PySpark and AWS Glue, along with strong proficiency in SQL for data manipulation. Capable of designing scalable data lakes and optimizing data workflows while ensuring data quality and availability.

Highest-signal resume keywords

PySparkAWS GlueSQLGitAWS Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL DevelopmentData TransformationDatabase OptimizationData VisualizationData Processing

Soft Skills

Problem-SolvingAttention to DetailCommunicationCollaborationTask Management

Tools & Technologies

Amazon S3Amazon DynamoDBAmazon QuickSightAWS Cloud ServicesAWS Step Functions

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Data Science

Industry Keywords

Data EngineeringData LakesData QualityData AvailabilityVersion Control

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudDynamoDBETLPySparkPythonSQL

About the role

Key responsibilities & impact

Develop and maintain ETL pipelines using PySpark and AWS Glue to process and transform large volumes of data efficiently.
Collaborate with analysts to understand data requirements and ensure data availability and quality.
Write and optimize SQL queries for data extraction, transformation, and loading.
Utilize Git for version control, ensuring proper documentation and tracking of code changes.
Design, implement, and manage scalable data lakes on AWS, including S3, or other relevant services for efficient data storage and retrieval.
Develop and optimize high-performance, scalable databases using Amazon DynamoDB.
Proficiency in Amazon QuickSight for creating interactive dashboards and data visualizations.
Automate workflows using AWS Cloud services like event bridge, step functions.
Monitor and optimize data processing workflows for performance and scalability.
Troubleshoot data-related issues and provide timely resolution.
Stay up-to-date with industry best practices and emerging technologies in data engineering.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Data Science, or a related field. Master's degree is a plus.
Strong proficiency in PySpark and Python for data processing and analysis.
Proficiency in SQL for data manipulation and querying.
Experience with version control systems, preferably Git.
Familiarity with AWS services, including S3, Redshift, Glue, Step Functions, Event Bridge, CloudWatch, Lambda, Quicksight, DynamoDB, Athena, CodeCommit etc.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills to work effectively within a team.
Ability to manage multiple tasks and prioritize effectively in a fast-paced environment.

Benefits

Comp & perks

Join our team and contribute to our mission of turning data into actionable insights.