Engineer, Data Engineering (Aguascalientes)

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