Data Engineer with less than a year in AWS & Spark
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Assessing your cultural and operational fit
Data Engineer with strong experience in building data pipelines, ETL processes, and big data systems. Proficient in AWS, Python, SQL, Spark, and Hadoop ecosystem. Skilled in data integration, transformation, and enabling predictive and diagnostic analytics. Adept at collaborating with data scientists, architects, and client technology teams to deliver reliable and high-quality data solutions.
Pune university
Bachelor's Degree · Cloud Computing
N/A – June 30, 2026
Unknown Company
Data Engineer
February 1, 2026 – Present
Pune, Maharashtra, India
CI/CD Pipeline using AWS
December 1, 2025 – January 31, 2026
Designed and implemented a CI/CD pipeline using AWS CodePipeline, CodeBuild, and CodeDeploy to automate application build, test, and deployment. Integrated with GitHub for source control and deployed the application on AWS EC2, improving deployment speed and reducing manual errors.
Cultural Fit Analysis
The candidate's project experience includes a CI/CD pipeline on AWS, demonstrating an interest in modern DevOps practices. The listed skills cover a broad range of data engineering tools and technologies, indicating adaptability. The current role as a Data Engineer aligns directly with the target role. However, the limited project diversity (only one listed) and the very recent start date of the professional experience (Feb 2026, implying a future start or very short tenure) make a deep assessment of cultural fit challenging. The education is also ongoing until 2026.
Soft Skills & Operational Fit
The candidate's resume indicates collaboration with data scientists and architects for pipeline optimization, suggesting an ability to work in a team. The project on CI/CD pipeline implementation shows an understanding of automation and operational best practices. However, without psychometric or English test results, a comprehensive assessment of soft skills and operational fit is not possible.