Data Engineer – AWS

YASH Technologies

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

Posted 9/18/2026full-timeIndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines on AWS, with advanced proficiency in Python and SQL for data transformation. Strong understanding of Snowflake architecture and experience with data warehousing solutions, ensuring data quality and security throughout the pipeline.

Highest-signal resume keywords

AWS Cloud ServicesSnowflake ArchitecturePython ProgrammingSQL ProficiencyData Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData TransformationPerformance TuningData ModelingGraph DatabasesVector DatabasesVersion Control (Git)Agile MethodologiesData GovernanceReal-Time Data Processing

Soft Skills

Analytical SkillsProblem-SolvingCommunicationCollaboration

Tools & Technologies

AWS S3AWS GlueAWS LambdaAWS RedshiftAWS EMRSnowflakeNeo4jMilvusAmazon OpenSearchAWS Step Functions

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Engineering

Industry Keywords

Data PipelinesData WarehousingAI WorkflowsData QualityData IntegrityData SecurityNVIDIA EcosystemRAPIDS LibrariesCUDA ToolingKafka

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureCloudKafkaNeo4jPythonSparkSQL

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

3-5 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
Hands-on experience with graph databases such as Neo4j or Neptune
Hands-on experience with vector databases such as Milvus or Amazon OpenSearch
Experience with version control systems such as Git and Git workflows
Experience working with Azure DevOps boards for backlog management in Agile environments
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Excellent analytical and problem-solving skills
Strong communication and collaboration abilities
Knowledge of the NVIDIA ecosystem and its applications in data and AI (nice to have)
Exposure to RAPIDS libraries or CUDA-based tooling for GPU-accelerated data processing (nice to have)
Experience with orchestration tools such as AWS Step Functions (preferred)
Familiarity with data governance and compliance practices (preferred)
Exposure to real-time data processing frameworks such as Kafka or Spark Streaming (preferred)

Benefits

Comp & perks

Flexible work arrangements
Career-oriented skilling models
Continuous learning, unlearning, and relearning opportunities
Stable employment
Inclusive team environment
Ethical corporate culture
Great atmosphere
Open collaboration
Support needed for realization of business goals