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Data Engineer – Python
YASH Technologies. Design, develop, and maintain scalable data pipelines using Python and SQL .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing scalable data pipelines using Python and SQL, with a strong focus on ETL/ELT processes and data quality frameworks. Proficient in leveraging cloud platforms like AWS or Azure to build modern data solutions and optimize performance for large-scale datasets.
Highest-signal resume keywords
Expert-Level Python ProgrammingStrong SQL and Database Design ConceptsETL/ELT Development ExperienceData Pipeline Development and OrchestrationGit Version Control
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonSQLETLELTData Pipeline DevelopmentData ValidationData Quality FrameworksLinux/Unix ScriptingPySparkApache Airflow
Tools & Technologies
AWSAzurePower BISnowflakeSQL ServerPostgreSQLRedshiftREST APICI/CDDevOps
Industry Keywords
Data EngineeringData WarehousingBig DataData TransformationData CleansingData ModelsAnalytical DatasetsMonitoringLoggingProduction Workloads
Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSAzureCloudETLLinuxPostgresPySparkPythonSparkSQLUnix
About the role
Key responsibilities & impact- Design, develop, and maintain scalable data pipelines using Python and SQL
- Build and optimize ETL/ELT processes for structured and unstructured data
- Develop data ingestion frameworks from APIs, databases, files, and cloud storage
- Perform data transformation, cleansing, validation, and quality checks
- Work with AWS or Azure cloud platforms to build and support modern data solutions
- Design and maintain data models, data marts, and analytical datasets
- Optimize data pipeline and database query performance
- Implement monitoring, logging, and operational support for production workloads
- Collaborate with Power BI, Data Science, and application teams to deliver business solutions
- Follow best practices for version control, code reviews, CI/CD, and automated testing
Requirements
What you’ll need- 4–6 years of experience in Data Engineering
- Bachelor's degree in Computer Science, Information Technology, Engineering, or related field
- Expert-level Python programming
- Strong SQL and database design concepts
- ETL/ELT development experience
- Data pipeline development and orchestration
- Data validation and data quality frameworks
- Git version control
- Linux/Unix scripting
- PySpark / Apache Spark
- Apache Airflow or equivalent scheduling tools
- Data warehousing concepts
- Snowflake, SQL Server, PostgreSQL, Redshift, or similar platforms
- REST API integration
- Experience handling large-scale datasets and big data workloads
- Experience with Power BI reporting datasets and semantic models
- Exposure to real-time or near real-time data processing
- Knowledge of CI/CD pipelines and DevOps practices
- Experience supporting production data platforms
Benefits
Comp & perks- Flexible work arrangements
- Career-oriented skilling models
- Continuous learning, unlearning, and relearning
- Stable employment
- Great atmosphere and ethical corporate culture
- Inclusive team environment
- Support needed for realization of business goals