Data Engineer, Go To Market; Remote

About the Role

We are seeking a seasoned Data Engineer to join our team. You will be responsible for architecting and building robust data frameworks that empower Operational Data Store / Enterprise Data Lake Platforms. This role requires a blend of high-level technical expertise in modern data stacks and the ability to collaborate independently with stakeholders to translate business needs into scalable data solutions.

• 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 Git Hub.
• 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.

• 5+ 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, 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 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 Git Hub, etc.
• Experience identifying and solving issues concerning data management to improve data quality, and clean, prepare and optimize data for ingestion and consumption.
• Will work with Data Engineering teammates to review design, code, and test plans to increase knowledge and application of key frameworks and methodologies.
• 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.

• Market leader in compensation and equity awards.
• Comprehensive physical and mental wellness programs.
• Competitive vacation and holidays for recharge.
• Paid parental and adoption leaves.
• Professional development opportunities for all employees regardless of level or role.
• Employee networks, geographic neighborhood groups, and volunteer opportunities to build connections.
• Vibrant office culture with world‑class amenities.
• Great Place to Work Certified™ across the globe.

The base salary range for this position for all U.S. candidates is $100,000 - $155,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.

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