Emerging Data Engineer: ETL/ELT & Cloud Pipelines

re-zoo-me; Philadelphia, Northern (Philadelphia County, KY); Hybrid; USD 75,000 - 83,000; Full time

Benefits offered by this job

Paid time off

Medical, dental, and vision coverage

401(k) or RRSP retirement plans

Job summary

Capgemini is seeking an Associate Data Engineer in a hybrid role based in Philadelphia or Reading, PA. You will design, develop, test, and maintain data integration solutions and pipelines, ensuring data quality and governance while supporting cloud migration initiatives.

The role involves collaborating with solution architects and senior data engineers within Agile delivery teams, developing SQL queries, and contributing to data validation and testing efforts.

Qualifications

• Bachelor's degree or higher in a technical field.
• Experience with ETL/ELT data integration.
• Familiarity with data governance and data quality concepts.

Responsibilities

• Develop and maintain ETL/ELT jobs and data pipelines.
• Perform data extraction, transformation, and loading from multiple sources.
• Develop SQL queries and scripts to support analytics.
• Support UAT and issue resolution in Agile teams.

Skills

SQL development

Python basics

Relational databases

ETL/ELT concepts

Data warehousing concepts

Data quality

Agile methodologies

Airflow/Data Factory

Cloud platforms (Azure/AWS/GCP)

Spark/Hadoop/Kafka

DevOps/DataOps

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or related field

Tools

Snowflake

Azure Synapse

Databricks

BigQuery

Redshift

Airflow

Job description

Capgemini is seeking an Associate Data Engineer in a hybrid role based in Philadelphia or Reading, PA. You will design, develop, test, and maintain data integration solutions and pipelines, ensuring data quality and governance while supporting cloud migration initiatives.

The role involves collaborating with solution architects and senior data engineers within Agile delivery teams, developing SQL queries, and contributing to data validation and testing efforts.