Marketing Data & Analytics is building the Marketing data foundation on the company's Databricks Data Intelligence Platform: governed, certified datasets that power reporting, self-service analytics, and data science across Enterprise Marketing. The Data Engineer designs, builds, and operates the pipelines behind that foundation, from source ingestion through certified Delta tables in Unity Catalog, and keeps them reliable, documented, and cost-efficient in production.

Databricks is our core data engineering platform, and we are looking for an engineer with strong, hands-on Databricks experience who holds the Databricks Certified Data Engineer Associate or Professional credential. Just as important is how you work: you communicate clearly and concisely, you are a genuine team player across sites and time zones, and you stay humble, curious, and eager to learn and grow with the platform and the team. 

Design, build, and operate batch and incremental data pipelines on Databricks using Delta Lake, Unity Catalog, Databricks Workflows, PySpark, and SQL

Ingest data from enterprise systems, SaaS platforms, files, and APIs; apply standardization, data-quality checks, and business rules to produce certified, well-modeled tables that analysts, data scientists, and self-service tools consume

Write efficient, readable SQL and Python; tune performance and cost; follow the medallion architecture and the team's modeling and naming standards

Implement monitoring, alerting, runbooks, and rerun procedures so every production pipeline has a clear owner and a tested recovery path

Participate in code review, version control, CI/CD, and production promotion with the Platform team; document what you build so others can run and extend it

Partner with analysts, data scientists, and the Data Architecture and Data Governance leads to translating requirements into pipeline designs, and with the Data Steward on access, classification, and data-handling rules

Use approved AI-assisted development tools (Databricks Genie, Claude Code, Cursor) to accelerate development and documentation, with careful review of generated code

Contribute to team standards, share what you learn, and help onboard and mentor teammates

Databricks Certified Data Engineer Associate or Professional, with 3+ years of hands-on Databricks experience (Delta Lake, Unity Catalog, Workflows, PySpark, Databricks SQL) in production

Strong SQL, including window functions, incremental and merge patterns, and performance tuning on large tables

Python for data engineering (PySpark or pandas), API integration, and file processing

Experience running pipelines in production: monitoring, incident handling, root-cause analysis, and documentation

Excellent and concise communication explains technical work in plain language, writes clear documentation and status updates, and keeps stakeholders informed without being asked

Team player: collaborates across U.S. and ABC sites, shares credit, asks for and offers help, and puts the team's delivery ahead of individual preference

Humble and growth-minded: welcomes feedback and code review, learns new tools and domains quickly, and grows into broader responsibility over time

Attention to detail and ownership of data quality; comfort working within a regulated environment's privacy, access, and change-control requirements

Experience with Salesforce, Salesforce Marketing Cloud, web analytics, or other marketing and customer data sources

Familiarity with dimensional modeling frameworks, data-quality tooling, and metric or semantic layers

Exposure to entity matching or master-data concepts

Financial services or other regulated-industry experience

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience