Data Engineer – Marketing Technology

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, maintain, and enhance ETL/ELT pipelines for Salesforce, HubSpot, NetSuite, Stripe, DealHub, LMS, and Databricks.

• Create PySpark and SQL pipelines within Databricks notebooks adhering to established development standards.

• Manage data synchronization between Databricks and HubSpot, including data enrichment and marketing engagement processes.

• Construct and sustain Exchange layer pipelines for integration with external systems.

• Develop scheduled batch jobs and event-driven integrations utilizing REST, webhooks, and OAuth.

• Oversee pipeline health, configure alerts for failures and data quality, and resolve incidents as they arise.

• Keep documentation up-to-date regarding data flows, integration architecture, and troubleshooting guides.

• Create dimensional models, curated tables, and data marts within Databricks.

• Execute identity resolution, deduplication, validation, quality monitoring, normalization, and null handling processes.

• Assist with audience segmentation, lifecycle marketing, personalization, email deliverability, subscription management, and suppression-list synchronization.

• Establish integrations and transformation logic across marketing, sales, and operational systems.

• Facilitate website form and lead-capture processes along with third-party enrichment integrations.

• Maintain the infrastructure necessary for campaign attribution, channel analysis, funnel reporting, conversion analytics, lead-source tracking, and marketing ROI assessment.

• Collaborate effectively with demand generation, product marketing, sales operations, digital marketing, sales, IT, stakeholders, and data analysts.

⛳️ Requirements

• 5+ years of experience in data engineering with practical experience in pipeline development and production operations.

• Strong expertise in SQL and Python/PySpark.

• Experience in constructing and managing ETL/ELT pipelines using Databricks, dbt, Airflow, Azure Data Factory, or similar tools.

• Hands-on experience with cloud data platforms like Databricks, Snowflake, BigQuery, or Redshift.

• Comprehensive understanding of dimensional data modeling, including fact tables, dimension tables, schema design, and data warehouse principles.

• Familiarity with medallion or layered data architectures, Kimball-style star schemas, and one-big-table data modeling approaches.

• Knowledge of REST, webhooks, OAuth, and batch synchronization architectures.

• Experience with CRM platforms like Salesforce or HubSpot, marketing automation systems, and CPQ/quoting tools such as DealHub or similar.

• Bachelor’s degree in Computer Science, Information Systems, or relevant industry experience.

🏝️ Benefits

• Engage in high-impact work that directly supports marketing operations and scalability.

• Utilize a modern technology stack consisting of Databricks, Delta Lake, PySpark, HubSpot, Python, and SQL.

• Opportunity to influence data infrastructure during a significant platform migration.

• Work in a collaborative, cross-functional environment alongside marketing, sales, and IT teams.

• Experience an inclusive workplace with equal opportunity employment.