Junior Data Engineer - Cloud Pipelines & BI

VML Enterprise Solutions; Austin (TX); On-site; USD 60,000 - 90,000; Full time

Job summary

MAP | WPP Enterprise Solutions in Austin, TX, is seeking an Associate Data Engineer to join our growing Data Insights and Science team. You will learn to build data pipelines, work with Python and SQL, and collaborate with engineers, data scientists, and analysts to deliver reliable analytics solutions.

Ideal candidates have 0–2 years in data engineering or related fields, familiar with cloud platforms (GCP/AWS/Azure), and hands-on with dbt, Airflow, BigQuery or Snowflake.

Qualifications

• 0–2 years of experience in data engineering or related field.
• Strong programming in Python, SQL or Scala.
• Understanding of ETL/ELT and relational databases.
• Familiarity with cloud platforms (GCP, AWS, Azure) and modern data stack tools.
• Version control with GitHub/Git.
• Strong analytical skills and English proficiency.

Responsibilities

• Assisting in identifying, collecting, and integrating data from various sources by building and maintaining data pipelines and models for BI/analytics.
• Writing clean SQL and code (Python, Spark, etc.) to optimize data workflows under senior guidance.
• Helping monitor daily ETL flows and data quality tools.
• Assisting in troubleshooting, debugging, and resolving data pipeline incidents.
• Collaborating with CRM developers, data scientists, data analysts, and product owners to deliver high-quality data.
• Learning best practices in cloud data architecture, migrations, and data management.

Skills

Python

SQL

ETL/ELT

Git

English communication

Education

Data engineering degree or CS degree

Tools

dbt

Airflow

BigQuery

Snowflake

Job description

MAP | WPP Enterprise Solutions in Austin, TX, is seeking an Associate Data Engineer to join our growing Data Insights and Science team. You will learn to build data pipelines, work with Python and SQL, and collaborate with engineers, data scientists, and analysts to deliver reliable analytics solutions.

Ideal candidates have 0–2 years in data engineering or related fields, familiar with cloud platforms (GCP/AWS/Azure), and hands-on with dbt, Airflow, BigQuery or Snowflake.