Senior ETL Data Engineer & Data Warehouse Architect

Experian; California (MO); On-site; USD 183,851 - 202,276; Full time

Job summary

Experian is seeking an expert ETL Data Engineer to design and implement data pipelines, warehouses, and analytics tools to democratize data. You will partner with PMs, architects, and data scientists to translate requirements into scalable data services and analytics solutions.

You will lead data engineering initiatives, tackle performance challenges, and enable a self-service BI Platform in collaboration with BI engineers. Telecommuting may be available where appropriate.

Qualifications

• Bachelor's degree in Computer Science, Electronics Engineering or related field and 7 years of experience.
• Experience building scalable Big Data solutions with Hadoop, Spark, and Kafka.
• Experience handling petabyte-scale data and optimizing ETL for performance and cost.
• SQL and Python for data analysis, ML model development, and automation.
• AWS ecosystem: data lakes on S3, ETL on EMR, data warehouses on Redshift.
• BI tools such as Tableau and Alteryx for dashboards and insights.

Responsibilities

• Build data pipelines and data warehouses for large-scale analytics.
• Develop scalable ETL pipelines ingesting data from internal and external sources.
• Partner with PMs, architects, engineers, and data scientists to understand requirements.
• Lead and mentor a data engineering team with an inspiring leadership style.
• Troubleshoot data, system, and performance issues; participate in on-call rotation.

Skills

SQL

Python

Big Data concepts

Leadership

Education

Bachelor's degree in Computer Science or related field

Tools

Apache Hadoop

Apache Spark

Kafka

AWS (S3, EMR, Redshift)

Tableau

Alteryx

Job description

Experian is seeking an expert ETL Data Engineer to design and implement data pipelines, warehouses, and analytics tools to democratize data. You will partner with PMs, architects, and data scientists to translate requirements into scalable data services and analytics solutions.

You will lead data engineering initiatives, tackle performance challenges, and enable a self-service BI Platform in collaboration with BI engineers. Telecommuting may be available where appropriate.