Enterprise AWS Data Architect: Lakehouse, ETL & BI

EROS Technologies Inc; Alameda (CA); Sur place; USD 140 000 - 200 000; Plein temps

Résumé du poste

EROS Technologies Inc in Alameda, CA is seeking an experienced Enterprise Data Architect to design and govern scalable AWS data platforms that align with business strategy.

You will lead the architecture and implementation of data lakes/lakehouse solutions using AWS services, oversee robust ETL/ELT pipelines, and define enterprise data models to support analytics and reporting. The role also includes BI standards with Tableau, security, and CI/CD across data ecosystems.

Qualifications

• Experience designing enterprise data architectures on AWS.
• Knowledge of data lakes/lakehouses and orchestration.
• Ability to design dimensional models (Star/Snowflake).
• Experience building robust ETL/ELT pipelines (batch and real-time).
• Strong SQL and Python/PySpark proficiencies.

Responsabilités

• Architect and oversee implementation of data lakes/lakehouse solutions on AWS.
• Lead design of ETL/ELT pipelines for high quality, reliable data.
• Define enterprise data models and BI architecture standards with Tableau governance.
• Mentor data engineers and BI developers; drive coding and architecture standards.
• Ensure data governance, security, and CI/CD practices across data platforms.

Connaissances

SQL

Python

PySpark

Data modeling

ETL/ELT

AWS

Tableau

CI/CD

Terraform

CloudFormation

Jira

Data governance

Security IAM

Outils

S3

Glue

Redshift

Athena

EMR

Lake Formation

Tableau

Terraform

CloudFormation

Description du poste

EROS Technologies Inc in Alameda, CA is seeking an experienced Enterprise Data Architect to design and govern scalable AWS data platforms that align with business strategy.

You will lead the architecture and implementation of data lakes/lakehouse solutions using AWS services, oversee robust ETL/ELT pipelines, and define enterprise data models to support analytics and reporting. The role also includes BI standards with Tableau, security, and CI/CD across data ecosystems.