Remote AWS Data Engineer — Data Pipelines & Analytics

Bright Vision Technologies; Frisco (TX); A distancia; USD 115.000 - 165.000; Jornada completa

Descripción de la vacante

Bright Vision Technologies seeks an AWS Data Engineer to design, build, validate, and support data solutions for enterprise operations, analytics, and decision-making. You will work with AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, Python, SQL, and orchestration to deliver reliable, maintainable data pipelines.

You will collaborate with cross-functional teams and implement data governance, quality checks, and scalable data processing across the lifecycle, enabling trusted information for

Formación

• 4+ years of professional data engineering experience.
• Hands-on experience with AWS S3, Glue, Redshift, Athena, EMR, Lake Formation.
• Proficient in Python and SQL for data processing and analytics.
• Strong knowledge of data modeling, ETL/ELT, and data governance.
• Ability to translate business requirements into scalable data solutions.
• Excellent communication and collaboration skills.

Responsabilidades

• Develop and maintain data pipelines, transformations, and data models.
• Translate source-to-target and business requirements into validated data solutions.
• Implement data quality checks, access controls, monitoring, and recovery procedures.
• Tune SQL and processing jobs for performance and cost efficiency.
• Document data definitions, lineage, procedures, and architectural decisions.

Conocimientos

SQL

Python

Data modeling

ETL/ELT

Data governance

Herramientas

AWS S3

AWS Glue

Redshift

Athena

EMR

Lake Formation

Data pipeline orchestration

Descripción del empleo

Bright Vision Technologies seeks an AWS Data Engineer to design, build, validate, and support data solutions for enterprise operations, analytics, and decision-making. You will work with AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, Python, SQL, and orchestration to deliver reliable, maintainable data pipelines.

You will collaborate with cross-functional teams and implement data governance, quality checks, and scalable data processing across the lifecycle, enabling trusted information for