Data Engineer

About the company

• Collaborative engineering team building data infrastructure for marketing operations and go-to-market strategy in a fast-growing global software environment.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines using medallion architecture (Bronze, Silver, Gold)
• Integrate data from Salesforce, HubSpot, NetSuite, Stripe, DealHub, LMS into Databricks
• Develop data transformations using Python, PySpark, and SQL
• Manage data synchronization between Databricks and HubSpot
• Build Exchange layer pipelines for external systems
• Develop scheduled batch jobs and event-driven integrations using REST APIs, webhooks, OAuth
• Monitor pipeline performance and implement alerts
• Document data flows, integration architecture, operational procedures
• Build dimensional data models (fact, dimension, bridge tables)
• Implement identity resolution, deduplication, normalization, validation
• Establish data quality checks and freshness monitoring
• Support campaign attribution, channel performance analysis, funnel reporting

Requirements

• At least 5 years of experience in data engineering
• Strong proficiency in SQL and Python/PySpark
• Experience with Databricks, dbt, Airflow, Azure Data Factory, or equivalent
• Hands-on experience with Databricks, Snowflake, BigQuery, or Amazon Redshift
• Understanding of dimensional data modeling and data warehouse concepts
• Experience with medallion architectures, Kimball star schemas
• Knowledge of API integration patterns (REST, webhooks, OAuth)
• Experience with CRM platforms (Salesforce, HubSpot), marketing automation, CPQ tools
• Bachelor's degree in Computer Science or related field

Conditions

• Fully remote work
• Competitive compensation and benefits
• Professional development opportunities
• International collaboration