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Senior Software Engineer – AWS Glue, Python, SQL
YASH Technologies. Design, build, and maintain scalable data pipelines and ETL/ELT processes .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining scalable data pipelines and ETL/ELT processes, with strong proficiency in Python and SQL for data transformation and reporting. Familiarity with AWS services and insurance industry data enhances the ability to deliver accurate and reliable data solutions.
Highest-signal resume keywords
Python ProgrammingSQL Query OptimizationAWS Data Pipeline DevelopmentData Analysis and ProfilingInsurance Industry Knowledge
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DesignETL/ELT ProcessesData TransformationData ValidationData ModelingRelational DatabasesData Quality ChecksTroubleshooting Data IssuesData WarehousingBusiness Intelligence Tools
Soft Skills
Strong Communication SkillsCollaboration Across TeamsAbility to Manage Multiple Priorities
Tools & Technologies
AWS S3AWS GlueAWS LambdaAWS RedshiftAWS AthenaAWS CloudWatch
Industry Keywords
Insurance DataPolicy DataClaims DataBilling DataCustomer DataUnderwriting Data
Tech Stack
Tools & technologiesAmazon RedshiftAWSCloudETLPythonSQL
About the role
Key responsibilities & impact- Design, build, and maintain scalable data pipelines and ETL/ELT processes
- Develop and optimize Python and SQL code for data ingestion, transformation, validation, and reporting
- Build and support cloud-based data solutions on AWS using Amazon S3, AWS Glue, Lambda, Redshift, and Athena
- Analyze data to identify trends, anomalies, quality issues, and opportunities for improvement
- Work with analysts, product owners, and business stakeholders to understand requirements and deliver trusted data
- Apply data quality checks, monitoring, and documentation to ensure data is accurate, secure, and reliable
- Troubleshoot pipeline and data issues, identify root causes, and implement lasting fixes
- Follow security, governance, and compliance practices when handling sensitive data
Requirements
What you’ll need- 4–6 years of professional experience in data engineering or a closely related role
- Strong proficiency in Python and SQL, including writing and optimizing queries
- Hands-on experience designing and supporting data pipelines in AWS
- Experience with data analysis, data profiling, and validating results
- Knowledge of data modeling concepts and relational databases
- Insurance industry experience or a solid understanding of insurance data and business processes
- Strong written and verbal communication skills, including the ability to explain technical topics to nontechnical audiences
- Ability to collaborate across teams and manage multiple priorities
- Preferred: Experience with AWS services such as S3, Glue, Lambda, Redshift, Athena, and CloudWatch
- Preferred: Familiarity with insurance data such as policy, claims, billing, customer, or underwriting data
- Preferred: Experience with data warehousing, reporting, or business intelligence tools
- Preferred: Familiarity with version control, automated testing, and CI/CD practices
Benefits
Comp & perks- Flexible work arrangements
- Inclusive team environment
- Career-oriented skilling models
- Continuous learning, unlearning, and relearning opportunities
- Stable employment
- Support needed for realization of business goals
- Ethical corporate culture
- Great atmosphere