Senior Data Engineer: Real-Time Pipelines on GCP

Ulta Beauty; Chicago (IL); On-site; USD 103,000 - 140,000; Full time

Benefits offered by this job

Health benefits

Dental and Vision benefits

Life and Disability insurance

Paid time off

Job summary

Ulta Beauty is seeking a Senior Data Engineer to design and build scalable batch and real-time data pipelines on Google Cloud Platform and Databricks. You will collaborate with engineers, analysts and developers to deliver robust data solutions and ML/agentic AI capabilities that enhance guest experience.

The role requires 5+ years in data engineering, expertise in GCP/Databricks, and hands-on experience with BigQuery, Spark and streaming.

Qualifications

• Bachelor’s degree or applicable work experience in computer science or related field.
• 5+ years of development experience with GCP services, Databricks (GCP preferred) and exposure to AI agentic development capabilities.
• Deep understanding of large data warehouse ecosystems and platform re-platforming on Google Cloud and Databricks.
• Experience designing and developing data pipelines for batch and real-time ingestion using Spark streaming.
• Passion for new technologies, continuous improvement, and designing data solutions with monitoring and alerting policies.
• Proficiency in Java, Python or other scripting languages, and SQL/NoSQL databases.
• Experience with BigQuery, Databricks, Spark, Kafka Streams; testing and automation using Docker, GitHub, Jenkins and Unix/Linux shells.
• Hands-on in Enterprise Integration Patterns and coding best practices; proactive in issue detection and prevention.
• Strong work ethic, team player, and ability to operate in onshore/offshore models.

Responsibilities

• Design, develop, and support scalable batch and real-time data pipelines across GCP and Databricks.
• Build data engineering solutions on GCP using BigQuery, Dataflow, Cloud Composer/Airflow, GCS, Pub/Sub and related services.
• Develop and optimize Databricks pipelines with Spark, Delta Lake, notebooks, workflows, and Databricks SQL.
• Tune SQL, Spark, BigQuery, and Databricks workloads for performance and cost efficiency.
• Support automated deployment, code promotion, CI practices using Docker, GitHub, Jenkins and shell scripts.
• Collaborate with cross-functional teams to gather requirements and deliver quality results.
• Mentor junior engineers on data engineering best practices, cloud development, and data quality.
• Assist with POC evaluation, project estimation, performance testing, and large data set tuning.
• Provide production support and handle off-hours deployment needs and issue resolution.

Skills

Data engineering

GCP

Databricks

Python

Java

SQL

NoSQL

Spark

Docker

GitHub

Jenkins

Unix/Linux shell

Education

Bachelor’s degree in computer science or related field

Tools

BigQuery

Databricks

Spark

Kafka Streams

Docker

GitHub

Jenkins

Job description

Ulta Beauty is seeking a Senior Data Engineer to design and build scalable batch and real-time data pipelines on Google Cloud Platform and Databricks. You will collaborate with engineers, analysts and developers to deliver robust data solutions and ML/agentic AI capabilities that enhance guest experience.

The role requires 5+ years in data engineering, expertise in GCP/Databricks, and hands-on experience with BigQuery, Spark and streaming.