We’re looking for a Senior Technology Lead to help drive that build-out.

In this role, you’ll be a senior technical voice on the  partner marketing platform effort bringing the mix of Data Engineering, Software Engineering, Architecture, Data Modeling, and developing data ingestion patterns to support the Marketing Programs and AI orchestration. Along with engineering big picture, you will lead design for complex integrations, shape how the team builds and models to empower our marketing team in delivering best-in class marketing campaigns and API systems. You will also help us apply AI tooling – both in how we build and in what we build and help senior engineers level up.

In This Role, You Will:

• Lead the design and delivery of complex, end-to-end SFMC initiatives for partner marketing, such as journey and automation builds and NBA integration, with minimal day-to-day guidance.
• Own and architect the end-to-end data model for Salesforce Marketing Cloud and Salesforce Data Cloud (Data 360), including Data Extensions, Contact Builder/Data Designer relationships, Data Model Objects (DMOs), Data Lake Objects (DLOs), and Identity Resolution rulesets.
• Design and build a knowledge graph connecting partner, property, contact, and campaign entities across SFMC, Data Cloud, and upstream systems to enable unified partner profiles, relationship discovery, and Next Best Action (NBA) recommendations.
• Define the ontology, entity-relationship structure, and identity resolution/deduplication logic underpinning the knowledge graph and Data Cloud unified profiles.
• Design, develop, and optimize data capture, processing, storage, and distribution solutions that power marketing campaigns, reporting, and partner integrations.
• Build and maintain batch and streaming pipelines that are reliable, observable, and cost-efficient at scale.
• Model and curate datasets that marketing, analytics, and partner teams can trust and self-serve from.
• Expose data through well-designed APIs and services that integrate with internal platforms and third-party marketing tools.
• Use AI-assisted development tools in your day-to-day workflow, and help the team establish where they help and where they do not.
• Partner with the business to integrate AI and LLM capabilities into marketing data workflows enrichment, classification, content generation, and agentic automation—with appropriate evaluation and guardrails.
• Design and develop ETL/ELT pipelines end-to-end, from source system extraction (for example, PMDS, Salesforce Core CRM) through transformation and orchestration, into  Data Extensions, Data Cloud DMOs/DLOs, and the knowledge graph, including evaluating SFMC/Data Cloud-native data management versus custom pipelines.
•  EG’s external data lake (for example, AWS, EGDL), so data used for marketing can be queried in place without duplicating it, keeping it available outside for analytics and other downstream consumers.
• Establish data pipeline orchestration, scheduling, and monitoring (for example, Airflow, dbt, or similar), with clear SLAs for data freshness, identity resolution accuracy, and pipeline reliability, as the team scales from pilot to production volumes.
• Drive platform health and reliability practices (for example, change/release management, CI/CD for Salesforce metadata, monitoring and alerting) across SFMC and Data Cloud.
• Serve as a go-to technical resource for engineers and partner marketing stakeholders building on SFMC and Data Cloud, unblocking complex technical issues and reviewing designs and pull requests for platform-wide standards.
• Mentor other engineers on the team and share platform and data architecture knowledge through documentation to raise the team’s overall technical standards.
• Partner with partner marketing stakeholders, data science partners, and Salesforce (vendor) contacts to translate platform capabilities and constraints into practical implementation plans.

Experience and Qualifications:

• Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
• 10+ years of experience building and operating enterprise software platforms, with hands-on experience in Salesforce Data Cloud (Data 360, Automation Studio, Journey Builder, Content Builder, SSJS/AMPscript, SOAP/REST APIs) or comparable enterprise MarTech platforms.
• Demonstrated experience leading complex technical projects end-to-end within a team or domain, with minimal supervision.
• Experience with data integration patterns (for example, SFTP, SOAP/REST, Data Extensions, CDP/Data Cloud) connecting marketing platforms to upstream and downstream systems.
• Experience architecting data models for CRM or marketing platforms, such as Salesforce Marketing Cloud (Contact Builder/Data Designer, Data Extensions) and/or Salesforce Data Cloud (Data Model Objects, Data Lake Objects, Identity Resolution).
• Data engineering experience, including designing and building ETL/ELT pipelines end-to-end, data modeling for large-scale audience and contact datasets, and working with SQL and cloud data warehouses (for example, AWS, Snowflake, or similar) to move and transform partner data into marketing platforms.
• Strong proficiency in SQL and at least one programming language commonly used for data engineering (for example, Python, Scala, or Java), along with experience using data processing frameworks and orchestration tools (for example, Spark, Airflow, dbt, or similar).
• 5+ years of hands-on programming experience with Python, Java, or Scala.
• Strong SQL skills and a solid understanding of database design, data ingestion, modeling, and performance optimization.
• Demonstrable experience leveraging AWS services, including S3, Redshift, Lambda, Glue, DynamoDB, EC2, and AppFlow.
• Experience with batch and/or stream processing using Spark, Kafka, or SQS.
• Experience building with LLMs and GenAI services (for example Amazon Bedrock)—prompt design, retrieval/RAG patterns, vector stores, and evaluating output quality, cost, and latency.
• Experience using agentic AI for development and task orchestration – configuring, constraining, and reviewing agent-produced code and building custom skills/workflows to accelerate delivery.

• Are you interested in this position?

   

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