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Data Engineer with 3+ years in AWS ETL & Data Pipelines
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AWS Data Engineer with 3+ years of hands-on experience in designing, developing, and optimizing scalable ETL and data pipelines. Strong expertise in AWS services (S3, Glue, Lambda, Athena, SNS, SQS), Apache Airflow, Snowflake, and Apache Spark. Experienced in data migration, automation using Terraform, performance tuning, and ensuring data quality and governance. Proven ability to work in Agile teams and deliver reliable, production-grade data solutions.
Vignan's Nirula Institute of Technology and Science for Women
Bachelor of Technology · Information Technology
August 1, 2017 – June 30, 2021
Proclink Consulting Services LLP
Data Engineer
August 1, 2022 – Present
India
AWS Data Pipeline & Analytics Platform
June 28, 2026 – Present
Built end-to-end pipelines using AWS Glue, Athena, and Snowflake. Orchestrated workflows using Apache Airflow with retries, alerts, and SLA monitoring. Delivered curated datasets for analytics and reporting teams.
Event-Based File Processing System
June 28, 2026 – Present
Designed S3 → SQS → Lambda pipeline for scalable file processing. Ensured idempotency, failure handling, and metadata tracking.
Cultural Fit Analysis
The candidate's experience in Agile environments and collaboration with various stakeholders (data analysts, product teams) suggests a good cultural fit for dynamic, team-oriented roles. The diversity of projects, from event-based processing to end-to-end analytics platforms, indicates adaptability and a broad understanding of data engineering challenges. Their focus on data quality and reliability aligns with best practices in data-driven organizations.
Soft Skills & Operational Fit
The candidate demonstrates strong operational fit through their experience in implementing monitoring, logging, and error handling, which are crucial for maintaining reliable data pipelines. Their collaboration with Agile teams indicates good teamwork and communication skills. The detailed project descriptions suggest an ability to articulate technical solutions clearly.