AWS Data Engineer Profile Summary

Data Engineer with 2–5 years of experience designing, building, and maintaining cloud‑native data platforms on AWS. Background in developing scalable ETL/ELT pipelines, integrating multiple data sources, and supporting enterprise analytics environments. Experienced in delivering reliable, secure, and high‑performance data solutions with a focus on automation, scalability, and data quality.

Key Capabilities
Data Engineering
  • Cloud‑native data architectures on AWS, ETL/ELT pipeline development, data modeling, API and database integration, workflow orchestration.

AWS Services (Some)
  • Amazon S3, AWS Glue, Lambda, Redshift, Athena, EMR, Kinesis, IAM, CloudWatch, EventBridge.

Data Platforms & Tools
  • Apache Spark, Airflow, Snowflake (preferred), Databricks (preferred), Git/GitHub.

Programming
  • Python, SQL, REST APIs.

DevOps
  • CI/CD fundamentals, Docker basics, infrastructure automation exposure, version control with Git.

Soft Skills
  • Strong analytical and problem‑solving skills.
  • Clear communication with technical and business stakeholders.
  • Collaborative team player with a client‑oriented mindset.
  • Comfortable working in Agile environments.
  • Continuous learning mindset and passion for AWS technologies.

Experience

2–5 years of hands‑on experience building, deploying, and supporting AWS‑based data platforms and production‑grade data pipelines.

Preferred Certifications
  • AWS Certified Data Engineer – Associate
  • AWS Certified Solutions Architect – Associate
  • AWS Certified Developer – Associate
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Data Engineer (Engineer Database ) (Aguascalientes)

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