The Data Engineer - Marketing Technologies builds and maintains the data pipelines, models, and real-time streams that serve as the foundation for 7-Eleven’s Marketing Technology (MarTech) personalization, decisioning, and measurement capabilities. This role is responsible for making Customer 360 (C360) a reliable single source of truth, engineering batch and event-driven pipelines (including loyalty, promotion, and pump/transaction data), and delivering governed, well-documented customer attributes to downstream activation platforms. The Data Engineer partners with data science, architecture, MarTech engineering, and platform owners to close upstream data-quality, freshness, and coverage gaps that limit personalization today. This role directly enables timely, accurate, and compliant use of customer data across every marketing channel.

KEY DUTIES AND RESPONSIBILITIES:

• Design, build, and operate scalable batch and real-time data pipelines in Databricks and related tooling to support audience, personalization, and measurement use cases.
• Engineer event-driven streaming (e.g., Kafka) for loyalty, pump, and transaction events to enable near-real-time personalization.
• Build and maintain the Customer 360 data model, feature/attribute pipelines, and promotion/offer data feeds to decisioning systems.
• Implement data-quality validation, monitoring, and change management so segments, flags, and attributes are accurate and trustworthy.
• Deliver governed customer attributes and audiences to activation platforms (e.g., Hightouch, Salesforce Marketing Cloud) with clear ownership and documentation.
• Partner with data science to productionize model features and with architecture to align on data contracts and identity resolution.
• Support privacy and compliance requirements across all data flows.

EDUCATION AND EXPERIENCE:

EDUCATION: Bachelors/4 Yr Degree

YEARS OF RELEVANT WORK EXPERIENCE: 4+ years

CERTIFICATIONS / LICENSES: Databricks or cloud (AWS/Azure) certifications preferred.

SPECIFIC KNOWLEDGE AND SKILLS:

• Strong SQL and proficiency in a programming language for data engineering (e.g., Python or Scala).
• Hands-on experience with Databricks/Spark, data lake/warehouse design, and pipeline orchestration.
• Experience with real-time/streaming data (e.g., Kafka) and event-driven architectures.
• Experience with reverse-ETL/activation and identity resolution (e.g., Hightouch, LiveRamp/UID2) is a plus.
• Understanding of data modeling, data quality, governance, and change management.
• Familiarity with marketing/customer data concepts (C360, RFM, LTV, loyalty) and compliant handling of PII.

This job description is intended to describe the general nature and level of the work being performed by the individuals assigned to this job. This is not an exhaustive list of all duties and responsibilities. Management reserves the right to amend and change the duties and responsibilities of this job to meet business and organizational needs, as necessary.

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