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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing scalable ETL/ELT pipelines using AWS services, SQL, and Python. Proficient in data engineering practices, including data warehousing concepts, version control, and CI/CD methodologies.
Highest-signal resume keywords
ETL/ELT Pipeline DevelopmentSQL ProficiencyPython ProgrammingAWS Cloud ServicesData Warehousing Concepts
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
ETL/ELT Pipeline DevelopmentSQL ProficiencyPython ProgrammingData Warehousing ConceptsUnit TestingDebuggingData ModelingVersion Control (Git)CI/CD PipelinesWorkflow Orchestration (Apache Airflow)
Soft Skills
Analytical SkillsProblem-SolvingCommunication SkillsCollaborationTime Management
Tools & Technologies
Amazon RedshiftAWS LambdaAmazon S3AWS IAMAmazon CloudWatchAWS GlueSparkPySparkDatabricksAgile/Scrum
Certifications & Qualifications
AWS Certification
Industry Keywords
Data EngineeringData GovernanceAI/ML Data PipelinesFeature Engineering
Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSCloudETLPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Design, develop, and optimize scalable ETL/ELT pipelines for data ingestion and transformation
- Build and maintain robust data pipelines using AWS cloud services
- Partner with Business Intelligence, AI/ML, and Infrastructure teams to deliver reliable and scalable data platform solutions
- Develop efficient SQL queries and Python scripts for data processing, automation, and analytics
- Create and maintain technical documentation, including solution designs, data flow diagrams, and operational guides
- Develop unit tests and perform code reviews
- Monitor, troubleshoot, and optimize data pipelines for performance, scalability, and reliability
- Work on multiple projects simultaneously while managing priorities in a fast-paced environment
- Follow coding standards, best practices, and data governance guidelines
Requirements
What you’ll need- 3–5 years of hands-on experience in Data Engineering
- Strong experience designing and developing ETL/ELT pipelines
- Proficiency in SQL and Python programming
- Hands-on experience with Amazon Redshift, AWS Lambda, Amazon S3, AWS IAM, and Amazon CloudWatch
- Experience with AWS Glue preferred
- Experience with workflow orchestration tools such as Apache Airflow preferred
- Understanding of data warehousing concepts and dimensional data modeling
- Knowledge of version control systems such as Git
- Experience writing unit tests and following software development best practices
- Strong analytical, problem-solving, and debugging skills
- Excellent communication and documentation skills
- Ability to manage multiple tasks and work effectively in a collaborative environment
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
- Experience with CI/CD pipelines and DevOps practices preferred
- Knowledge of Spark, PySpark, or Databricks is an advantage
- Exposure to AI/ML data pipelines and feature engineering
- Familiarity with Agile/Scrum development methodologies
- Relevant AWS certification is an added advantage
Benefits
Comp & perks- Hybrid work arrangement
- Full-time employment