Software Engineer – Data Engineering

Caterpillar Inc.

. Design, develop, and maintain scalable data pipelines on AWS using services such as S3, Glue, Lambda, Redshift, and EMR .

Posted 10/28/2026full-timeBangalore • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines on AWS, utilizing services such as S3, Glue, and Redshift. Proficient in Python and SQL for data transformation, with a strong understanding of Snowflake architecture and data modeling concepts.

Highest-signal resume keywords

AWS Cloud ServicesSnowflake ArchitecturePython ProgrammingSQL ProficiencyData Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData TransformationPerformance TuningCI/CD PipelinesData WarehousingData GovernanceReal-Time Data ProcessingOrchestration ToolsGraph DatabasesVector Databases

Soft Skills

Analytical SkillsProblem-SolvingCommunicationCollaboration

Tools & Technologies

AWS S3AWS GlueAWS LambdaAWS RedshiftAWS EMRGitHub ActionsAzure DevOpsAWS Step FunctionsKafkaSpark Streaming

Industry Keywords

Data QualityData IntegrityData SecurityAgile EnvironmentsNVIDIA Ecosystem

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureCloudKafkaNeo4jPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Design, develop, and maintain scalable data pipelines on AWS using services such as S3, Glue, Lambda, Redshift, and EMR
Build and optimize data warehousing solutions using Snowflake, including performance tuning and data modeling
Write efficient and reusable code in Python and SQL for data transformation and processing
Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements
Monitor, troubleshoot, and improve pipeline performance and reliability
Ensure data quality, integrity, and security across all stages of the pipeline
Participate in code reviews, architecture discussions, and continuous improvement initiatives

Requirements

What you’ll need

5-8 years of experience in data engineering or related roles
Strong hands-on experience with AWS cloud services, including data and AI workloads
Deep understanding of Snowflake architecture, performance tuning, and best practices
Advanced proficiency in Python and SQL for data pipelines, transformations, and services
Strong understanding of graph and vector data modelling concepts and their practical applications
Experience developing and operating CI/CD pipelines (GitHub Actions) and cloud native deployments
Experience working with Azure DevOps (AzDO) boards for backlog management in Agile environments
Excellent analytical and problem-solving skills
Strong communication and collaboration abilities
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
Knowledge of the NVIDIA ecosystem and its applications in data and AI
Hands on experience with Vector (Milvus or similar) and Graph (Neo4J or similar) databases
Experience with orchestration tools such as AWS Step Functions
Familiarity with data governance and compliance practices
Exposure to real-time data processing frameworks (e.g., Kafka, Spark Streaming)