Customer Data Platform Data Engineer (Hybrid)
Signet Jewelers · Irving, TX · 2 wk ago
Information TechnologyFull-time
Responsibilities
- Design, build, and maintain scalable data pipelines to ingest, transform, and curate data within Adobe AEP and RTCDP.
- Develop and optimize complex SQL queries and data transformations for large-scale datasets.
- Design and maintain data models (conceptual, logical, and physical) that enable efficient analytics, segmentation, and activation use cases.
- Experience working with AWS data services such as S3, Redshift, Glue, and related tooling, including building and managing data pipelines from AWS-based source systems into Adobe AEP and RTCDP.
- Architect end-to-end solution designs leveraging AEP components such as XDM schemas, datasets, identities, profiles, and segmentation.
- Ensure high data quality, consistency, and governance across systems by implementing validation, monitoring, and error-handling mechanisms.
- Collaborate with business stakeholders, architects, and downstream consumers to understand requirements and deliver scalable data solutions.
- Tune performance and optimize pipelines for real-time and batch workloads within RTCDP.
- Document data architecture, data flows, and operational procedures.
- Support integrations with upstream and downstream systems including CRM, web/mobile, and other MarTech and analytics platforms.
- Demonstrate experience implementing data processing, automation, validation, and orchestration logic.
- Follow best practices for security, privacy, and compliance (PII handling, consent, and identity resolution).
Qualifications
- Expert-level SQL skills, with experience writing and optimizing complex queries.
- Strong Python programming experience for data engineering use cases.
- Proven experience as a Data Modeler, including dimensional and analytical data modeling.
- Hands-on experience designing and implementing solutions in:Adobe Experience Platform (AEP), Adobe Real-Time Customer Data Platform (RTCDP).
- Solid understanding of XDM schemas, datasets, identity stitching, profiles, and segmentation.
- Experience building batch and real-time data pipelines.
- Strong problem-solving and analytical skills.
- Ability to communicate technical concepts clearly to both technical and non-technical audiences.