Data Engineer – Go To Market

. Lead the full lifecycle of data engineering projects, from initial requirement gathering with stakeholders to production deployment and monitoring.

Posted 5/16/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $100,000 - $155,000 per yearWebsite

Tools & technologies

AirflowAmazon RedshiftApacheCloudJenkinsPythonSQL

Key responsibilities & impact

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.

What you’ll need

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 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.
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.

Comp & perks

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

ATS Keywords

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Hard Skills & Tools

data engineeringdata transformationsscripting languagesPythonSQLDBTApache Airflowdata modelingCI/CDdata validation

Soft Skills

stakeholder engagementstrategic decision-makingproblem-solvingcollaboration

Certifications

Bachelor's Degree in Computer ScienceBachelor's Degree in Information TechnologyBachelor's Degree in Computer Engineering