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Senior Software Engineer – AWS
YASH TechnologiesCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing ETL/ELT pipelines using PySpark and AWS services, ensuring data quality and governance throughout the data lifecycle. Proficient in implementing data models and frameworks that support analytics and compliance in cloud environments.
Highest-signal resume keywords
AWS Data Engineer ExperienceETL/ELT Pipeline DevelopmentAWS Glue ExpertiseData Governance KnowledgeAWS Certified Data Analytics – Specialty
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Develop robust ETL/ELT pipelines using PySpark, Glue, and Lambda for batch and near-real-time data ingestion and transformation
- Design logical and physical data models
- Implement schema evolution, partitioning strategies, and efficient metadata management
- Manage the complete data lifecycle from raw ingestion to curated and analytical layers
- Ensure data quality, lineage, and traceability
- Enable seamless data consumption by downstream systems such as Redshift Spectrum, QuickSight, SageMaker, and other BI platforms
- Enforce data governance, access control, and compliance through IAM, KMS, CloudTrail, and Lake Formation
- Implement and automate data validation frameworks using Deequ or Great Expectations
- Build infrastructure as code using AWS CDK or Terraform
- Orchestrate CI/CD pipelines with GitHub Actions or AWS CodePipeline
- Set up observability, performance tuning, and cost optimization through CloudWatch, Glue job optimization, and Athena query tuning
Requirements
What you’ll need- 4 to 7 years of experience as an AWS Data Engineer
- Proven experience architecting and implementing AWS data lake and analytics ecosystems
- Hands-on expertise in AWS Glue, S3, Athena, Lambda, Redshift, and Lake Formation
- Strong programming and ETL skills using PySpark / Python
- Deep understanding of data modeling, data ingestion patterns, and schema evolution
- Knowledge of data governance, security, and compliance frameworks in cloud environments
- Familiarity with CI/CD, IaC, and DevOps tools, including CDK, Terraform, GitHub Actions, and CodePipeline
- Experience with data quality frameworks such as Deequ and Great Expectations
- Strong problem-solving, analytical, and communication skills
- Experience in data migration and data modelling
- AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Associate
- Proven experience with database management systems and data warehousing
- Strong understanding of data governance and data quality principles
- Experience with data modelling tools and techniques
Benefits
Comp & perks- Flexible work arrangements
- Inclusive team environment
- Career-oriented skilling models
- Continuous learning, unlearning, and relearning opportunities
- Stable employment
- Great atmosphere and ethical corporate culture
- Open collaboration and transparent workplace
- All support needed for realization of business goals
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PySparkAWS GlueData ModelingETL SkillsData Quality FrameworksSchema EvolutionData Ingestion PatternsDatabase Management SystemsData WarehousingData Migration
Soft Skills
Problem-SolvingAnalytical SkillsCommunication Skills
Tools & Technologies
AWS LambdaRedshiftLake FormationGitHub ActionsAWS CodePipelineAWS CDKTerraformCloudWatchDeequGreat Expectations
Certifications & Qualifications
AWS Certified Data Analytics – SpecialtyAWS Certified Solutions Architect – Associate
Industry Keywords
Data GovernanceCompliance FrameworksData Quality PrinciplesCloud EnvironmentsCI/CDInfrastructure as CodeObservabilityPerformance TuningCost OptimizationBusiness Intelligence