Data Engineer, Go to Market (Remote)

CrowdStrike is a global leader in cybersecurity, dedicated to stopping breaches with advanced AI-native platforms. The Data Engineer will be responsible for architecting and building data frameworks that support operational data needs, collaborating with stakeholders to deliver scalable data solutions.

Responsibilities:

• Lead the full lifecycle of data engineering projects, from initial requirement gathering with stakeholders to production deployment and monitoring
• Design, develop and maintain complex data transformations, ensuring high data quality and performance using scripting languages like Python, Airflow, DBT and databases such as Snowflake or similar Data Lakes
• Build, scale, and maintain automated workflows using Apache Airflow to manage sophisticated data dependencies
• Maintain high engineering standards through CI/CD implementation and rigorous version control using GitHub
• Implement automated processes for data validation, ensuring high standards of data quality, accuracy, and integrity across all pipelines
• Act as a technical partner to the Analytics, Sales, and Marketing teams, building curated datasets that drive strategic decision-making

Requirements:

• 3+ years' experience in design & developing complex automation frameworks, queries, data modeling in SQL, Python, DBT, Apache Airflow
• Deep Experience in scripting languages such as Python and Cloud database experience such as Snowflake, Redshift, etc. to facilitate rapid ingestion and dissemination of key data
• Marketing Data Domain Expertise: Hands-on experience working with Marketing datasets including campaign performance data, lead, funnel stages and opportunity pipelines, and revenue attribution models
• Expertise in architecting scalable DBT projects using advanced modeling techniques, custom macros, complex Jinja-templated logic, and modular project structures to enforce DRY (Don't Repeat Yourself) principles across the enterprise
• Advanced proficiency in the DBT lifecycle including CI/CD processes such as Jenkins, Gitlab CI/CD etc., and source control tools such as GitHub, etc
• Experience identifying and solving issues concerning data management to improve data quality, and clean, prepare and optimize data for ingestion and consumption
• Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs
• Proven experience integrating and managing business data from enterprise applications into Semantic Layers to decouple complex logic from the BI layer to drive analytics and insights
• Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
• Marketing Automation Tools Knowledge: Experience with platforms such as Salesforce, Marketo, People.ai, Outreach and CRM systems for data integration and processing
• Understanding of machine learning concepts: Ability to collaborate with data science teams and support machine learning initiatives through data preparation, transformation and Feature store support