Context: Our end client is running a high-volume Salesforce Marketing Cloud programme across the US and Canada. We need to place five contractors across the delivery team. A strong emphasis on Salesforce Einstein AI capability is a hard requirement on the senior roles — this has been called out explicitly by the client so please make sure candidates can demonstrate hands-on experience, not just familiarity.
Systems Engineer (Salesforce Marketing Cloud) – ASAP Start
Role Overview We are looking for a data platform specialist to own Data Extension governance, SQL query development, Automation Studio monitoring, and SFTP data feed management. This role will directly support the MOPs Specialist on data-heavy tasks and ensure the underlying data quality that makes AI/Einstein scoring models accurate.
Engagement Details
- Commitment: 20 hours per week
- Location: US or Nearshore acceptable
Compensation (Hourly Rate)
- US-based candidates: Starting at $65 USD / hour.
- Nearshore candidates: Starting at $40 USD / hour.
- Note: All rates are highly flexible for exceptional candidates. You are encouraged to present candidates at their desired rate if they bring outstanding expertise.
What You Will Do
Your day-to-day focus will be on data platform operations, including:
- Data Extension schema design and governance.
- SQL query development for SFMC query activities.
- Automation Studio monitoring, including watchdog automations, error handling, and alert logging.
- SFTP and flat file data feed management.
- Supporting the senior MOPs Specialist on data-heavy journey and segmentation tasks.
AI & Data Hygiene Focus The primary AI relevance in this role is focused on data hygiene. Clean, deduplicated data is the absolute prerequisite for Einstein scoring models to produce accurate outputs. You must understand how data quality directly affects Einstein Engagement Scoring and Data Cloud unified profile integrity.
Skills & Experience Requirements
Must Have:
- Data Extension schema design
- Automation Studio monitoring
- SFTP / flat file data management
Strong Advantage:
- Deduplication workflow design and data hygiene automation
- Error alerting and logging
- Awareness of how data quality impacts Einstein Engagement Scoring accuracy
- Knowledge of Data Cloud unified profile hygiene for predictive model inputs
Nice to Have:
- Salesforce Data Cloud basics
- CASL data governance knowledge
