Associate Data Engineer: Build Data Pipelines & Analytics

Map; Austin (TX); On-site; USD 65,000 - 90,000; Full time

Job summary

MAP | WPP Enterprise Solutions is seeking an Associate Data Engineer to join the Data Insights and Science team in Austin. You will assist with building data pipelines and learning modern cloud data architectures while collaborating with engineers, data scientists, and product owners.

Ideal candidates have 0-2 years of data engineering experience or a related degree, and solid Python/SQL skills, plus familiarity with cloud tools and data stack technologies.

Qualifications

• 0-2 years experience or degree/bootcamp background in data engineering or related field.
• Strong Python, SQL, or Scala coding skills.
• Understanding of ETL/ELT and relational databases.
• Exposure to cloud platforms (GCP/AWS/Azure) and modern data stack tools.
• Familiar with version control using GitHub or Git.
• Strong analytical skills and clear communication in English.

Responsibilities

• Assist in identifying, collecting, and integrating data by building and maintaining data pipelines and models for BI/analytics.
• Write clean Python/SQL/Spark code to optimize data workflows under guidance.
• Monitor daily ETL flows and data quality tools.
• Troubleshoot data pipeline incidents and assist in debugging.
• Collaborate with CRM developers, data scientists, and product owners to deliver high-quality data.
• Learn best practices in cloud data architecture, migrations, and data management.

Skills

Python

SQL

Scala

ETL/ELT concepts

Cloud basics

dbt

Airflow

BigQuery

Snowflake

Git

English proficiency

Education

Degree or bootcamp in data engineering

Tools

dbt

Airflow

BigQuery

Snowflake

GitHub/Git

Job description

MAP | WPP Enterprise Solutions is seeking an Associate Data Engineer to join the Data Insights and Science team in Austin. You will assist with building data pipelines and learning modern cloud data architectures while collaborating with engineers, data scientists, and product owners.

Ideal candidates have 0-2 years of data engineering experience or a related degree, and solid Python/SQL skills, plus familiarity with cloud tools and data stack technologies.