About the job Marketing Data Engineer
Position Overview
The Marketing Data Engineer will build, optimize, and maintain DIVIETOs marketing data infrastructure and pipelines. This role works closely with the digital marketing, CRM, finance, and operations teams to collect, centralize, and model marketing performance data from multiple systems. The ideal candidate is a data specialist who understands marketing technologies (MarTech), ETL development, and analytics.
Key Responsibilities
Data Engineering & Integration
Design, build, and maintain automated ETL/ELT data pipelines from marketing platforms (Google Ads, Meta Ads, Mailchimp, HubSpot/CRM, Google Analytics, POS, loyalty systems).
Develop and manage data integrations using REST APIs, webhooks, and cloud data tools.
Consolidate structured & unstructured data into a unified marketing analytics warehouse.
Ensure data quality, integrity, and compliance across all pipelines.
Marketing Analytics
Build analytical datasets for campaign performance, customer segmentation, digital ROI, and brand growth.
Implement multi-touch attribution and lifetime value (LTV) models.
Support CRM and loyalty program analytics.
Forecast performance using modeling and predictive analytics.
Dashboards & Reporting
Build business intelligence dashboards (Power BI, Tableau, Looker, or Google Looker Studio).
Deliver weekly and monthly marketing performance insights.
Create dashboards for paid media, conversions, campaign attribution, and guest retention.
Communicate data findings to leadership and marketing teams.
Data Governance
Enforce data security and retention policies.
Ensure compliance with CCPA, CAN-SPAM, GDPR (where applicable).
Document data pipelines and reporting logic.
Required Qualifications
Bachelors degree in Data Engineering, Computer Science, Data Analytics, Statistics, or related field.
3+ years experience as a Data Engineer, Marketing Analyst, or Analytics Engineer.
Strong SQL development expertise.
Experience with ETL/ELT pipelines (Airflow, AWS Glue, Fivetran, dbt, Talend, or similar).
Familiar with marketing data sources: Google Analytics, Meta Ads, Google Ads, CRM, loyalty, POS systems.
Proficient with cloud data (AWS, Azure, or GCP).
Experience building dashboards (Power BI, Tableau, Looker).
Preferred Qualifications
Experience with Python (Pandas, NumPy, API requests).
Experience working with Salesforce or HubSpot CRM.
Familiar with Snowflake, BigQuery, or Redshift.
Experience supporting marketing attribution and growth frameworks.
Understanding of restaurant or eCommerce analytics is a plus.
Soft Skills
Strong communication and collaboration skills.
Ability to manage multiple projects independently.
Detail-oriented and highly analytical.
Problem-solving mindset with business intelligence awareness.
