Data Engineer - Real-Time Pipelines & Personalization

CBTS; Irving (TX); On-site; USD 115,000 - 140,000; Full time

Job summary

CBTS in Irving, TX seeks a data engineer to design, build, and operate scalable batch and real-time data pipelines using Databricks and related tooling. You will craft data models, feature pipelines, and marketing data feeds to support activation platforms and decisioning systems.

Collaboration with data science and architecture ensures robust identity resolution and governance. Applicants should have 3+ years in data engineering, strong SQL, Python/Scala, and hands-on Databricks/Spark

Qualifications

• 3+ years in a data engineering role with a focus on data pipelines and governance.
• Strong SQL and programming in Python or Scala.
• Experience with Databricks/Spark, data lake/warehouse design, and orchestration.
• Knowledge of real-time streaming (Kafka) and event-driven architecture.
• Familiarity with activation tools (Hightouch, LiveRamp UID2) and marketing data concepts.
• Understanding of PII handling, data privacy, and data quality disciplines.

Responsibilities

• Design, build, and operate scalable batch and real-time data pipelines.
• Maintain data models, feature pipelines, and marketing data feeds.
• Implement data-quality monitoring and governance across flows.
• Deliver governed attributes to activation platforms with clear ownership.
• Partner with data science and architecture on data contracts and identity resolution.
• Support privacy/compliance requirements across data flows.
• Prepare decision memos and metrics to drive cross-team alignment.

Skills

Data engineering (3+ years)

SQL

Python/Scala

Databricks/Spark

Data lake/warehouse design

Pipeline orchestration

Real-time data (Kafka)

Reverse-ETL/activation (Hightouch, UID

Tools

Databricks

Kafka

Hightouch

LiveRamp UID2

Salesforce Marketing Cloud

Contentstack / CMS & DAM

Job description

CBTS in Irving, TX seeks a data engineer to design, build, and operate scalable batch and real-time data pipelines using Databricks and related tooling. You will craft data models, feature pipelines, and marketing data feeds to support activation platforms and decisioning systems.

Collaboration with data science and architecture ensures robust identity resolution and governance. Applicants should have 3+ years in data engineering, strong SQL, Python/Scala, and hands-on Databricks/Spark