Sr. Marketing Data & AI Engineer

Mod Op•Dallas, TX

3d•Hybrid

About The Position

Mod Op's Marketing Data & AI Engineer is a specialized role at the intersection of marketing technology, customer data platforms, and applied AI. This individual brings strong marketing domain expertise and hands-on experience implementing CDPs, AI-driven marketing solutions, and enterprise platforms such as Salesforce and Marketo. The role is responsible for designing intelligent data pipelines, enabling real-time customer intelligence, and building AI/ML solutions that support consumer, product, and business marketing initiatives. This is a hybrid role with both remote work days and in-person work days at our Dallas-Fort Worth office location each week. The strongest candidates will be engineers who think like marketers and understand both how to build data pipelines and why marketing data matters. They recognize how CDPs enable personalization and how AI can improve campaign performance, customer acquisition, and retention. In this role, marketing domain credibility is as important as technical depth.

Requirements

3+ years of marketing domain experience required. Candidates should demonstrate fluency in marketing data concepts in addition to strong engineering skills.
Proven hands-on CDP implementation experience (Segment, Tealium, ActionIQ, Adobe Real-Time CDP, or similar enterprise platforms).
Direct experience with Salesforce Marketing Cloud, Salesforce Data Cloud, or Salesforce CRM data models.
Hands-on Marketo experience including data ingestion, program attribution, lead scoring, and API integration.
Strong understanding of marketing attribution models (multi-touch, data-driven, media mix modeling) and consumer journey analytics.
Cloud Expertise: GCP or AWS certification (Data Engineering or ML focus required); multi-cloud experience preferred.
Programming: Strong Python proficiency; experience with data science libraries and LLM/AI frameworks (LangChain, OpenAI APIs, Vertex AI).
Database Management: Advanced SQL across BigQuery, Teradata, Snowflake, and NoSQL databases (Cassandra, DynamoDB).
ML/AI: Working experience with ML workflows — model training, evaluation, deployment — across GCP/Azure/AWS services.
Marketing Tech Stack: Experience integrating with CDPs, CRMs, marketing automation platforms, and ad tech ecosystems (DSPs, Google Ads, Meta Ads APIs).
Data Visualization: Hands-on Google Looker and Tableau for marketing performance reporting and executive dashboards.

Nice To Haves

Experience with Salesforce Data Cloud or Marketing Cloud Intelligence (formerly Datorama).
Familiarity with ABM platforms (Demandbase, 6sense) and their data integration patterns.
Experience with Adobe Experience Platform (AEP) or other enterprise CDP/DMP environments.
Knowledge of Apache Spark, Airflow, or dbt for data orchestration and transformation.
Understanding of privacy-first data strategies including consent management, identity graphs, and cookie-less attribution.
Experience with Alteryx for marketing workflow automation and data preparation.
Exposure to data warehousing solutions (Snowflake, Redshift) in a marketing analytics context.
Strong understanding of data governance, security, and compliance as applied to marketing data (GDPR, CCPA).

Responsibilities

Design, implement, and maintain Customer Data Platform solutions integrating first-party, second-party, and third-party data sources.
Build identity resolution pipelines and unified customer profiles across online and offline touchpoints.
Architect data flows between CDPs, CRMs (Salesforce), marketing automation (Marketo), and downstream activation platforms.
Develop and optimize ETL/ELT pipelines in GCP, Azure, and AWS using Dataflow, Composer, Azure Synapse, and AWS Data Pipelines.
Design and deploy AI/ML models for customer segmentation, lead scoring, churn prediction, campaign recommendation, and content personalization.
Implement LLM-powered marketing workflows including campaign brief generation, audience insights summarization, and AI content classification.
Utilize GCP Vertex AI, Azure ML, and AWS SageMaker for model training, evaluation, and production deployment.
Apply Python and data science libraries (Pandas, NumPy, Scikit-learn, LangChain) for feature engineering and ML model development.
Develop and maintain bi-directional integrations between Salesforce (Sales Cloud, Marketing Cloud, Data Cloud) and enterprise data platforms.
Build Marketo data connectors for lead lifecycle management, program performance tracking, and marketing attribution.
Design CRM data models that support consumer, product, and business marketing use cases including pipeline influence and account health scoring.
Develop scalable pipelines for structured and unstructured marketing data including web analytics, email engagement, ad platform signals, and CRM events.
Optimize queries across SQL and NoSQL databases (BigQuery, Teradata, Cassandra, Snowflake, Databricks) for marketing analytics workloads.
Implement real-time streaming architectures (Pub/Sub, Kafka) for event-driven personalization and customer journey activation.
Build marketing performance dashboards in Google Looker and Tableau covering attribution, funnel analytics, campaign ROI, and audience insights.
Deliver self-service analytics capabilities for marketing teams with governed, reusable data models.
Partner with demand generation, product marketing, and consumer marketing teams to define and implement data-driven KPIs.