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Senior Data Engineer – Advertising
Truelogic Software. Design, build, and scale data pipelines and infrastructure for ingestion, transformation, storage, and serving .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and scaling data pipelines and infrastructure, with a strong focus on cloud data platforms and AI-enabled workflows. Proven ability to translate business needs into data solutions that deliver measurable value while mentoring teams and establishing engineering standards.
Highest-signal resume keywords
Data Engineering ExperienceCloud Data PlatformsPython and SQL ProficiencyAI-Powered CodingMLOps Tooling Familiarity
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DevelopmentETL ProcessesData GovernancePrivacy ComplianceSecurity Best PracticesVersion ControlTestingCode ReviewCI/CDAI/ML Integration
Soft Skills
Strong Communication SkillsMentoring ExperienceProcess Improvement Advocacy
Tools & Technologies
AWSGCPAzureGA4MLflowSageMakerVertex AICRMsCDPsVector Databases
Industry Keywords
Marketing Data EcosystemsComplex ProjectsCross-Functional CollaborationAgentic EngineeringAI-Enabled Workflows
Tech Stack
Tools & technologiesAWSAzureCloudETLGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Design, build, and scale data pipelines and infrastructure for ingestion, transformation, storage, and serving
- Collaborate with Machine Learning Engineering teams to support model training, evaluation, and serving
- Improve team processes, tooling, and ways of working
- Contribute to thought leadership, internal knowledge sharing, and community of practice efforts
- Translate business needs into product-minded data solutions that drive measurable business value
- Integrate marketing data sources such as GA4, advertising platforms, CRMs, and CDPs into reliable, well-modeled datasets
- Establish data engineering standards, documentation, and monitoring practices for data quality and reliability
- Apply AI-powered coding, agentic engineering, and AI-enabled workflows to accelerate delivery
- Lead technical workstreams and mentor other engineers
- Collaborate with cross-functional stakeholders on complex data challenges
Requirements
What you’ll need- 5+ years of data engineering experience, including building data pipelines and infrastructure from the ground up
- Deep expertise in cloud data platforms
- Proficiency in Python and SQL for data processing and ETL
- Experience building and deploying data workloads in AWS, GCP, or Azure
- Strong product orientation and ability to deliver measurable business value
- Hands-on experience with AI-powered coding, agentic engineering, and AI-enabled workflows
- Proven experience mentoring others and establishing engineering standards
- Familiarity with marketing data ecosystems including GA4, advertising platforms, CRMs, and CDPs
- Software engineering fundamentals including version control, testing, code review, and CI/CD
- Strong communication skills
- Experience with complex, ambiguous projects from definition through delivery
- Advanced English (B2 or higher)
- Experience with data governance, privacy compliance, and security best practices
- Experience integrating AI/ML capabilities into data pipelines and exposure to GenAI applications
- Familiarity with MLOps tooling such as MLflow, SageMaker, and Vertex AI, plus vector databases or RAG patterns
- Experience working across multiple verticals or client types
- Track record of advocating for and implementing process improvements
Benefits
Comp & perks- 100% Remote Work
- Highly Competitive USD Pay
- Paid Time Off
- Work with Autonomy
- Work with Top American Companies
- Engagement activities
- Work-life balance support
- Collaboration with a diverse, multicultural global network
- Access to seasoned senior talent and skilled professionals