Senior Data Engineer - Advertising
New
T
TruelogicAdvertising technology
Location: São Paulo; Workplace: RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Advanced English (B2 or higher)
- Experience
- 5+ years of data engineering experience
- Required Skills
- AWSPythonSQLETLGCPMicrosoft AzureData engineeringCI/CD
Requirements
- Have 5+ years of data engineering experience, including building data pipelines and infrastructure from the ground up.
- Bring deep expertise in cloud data platforms and the ability to assess which platforms work best and why.
- Be proficient in Python and SQL for data processing and ETL.
- Have experience building and deploying data workloads in AWS, GCP, or Azure.
- Have hands-on experience with AI-powered coding, agentic engineering, and AI-enabled workflows.
- Have experience mentoring others, establishing engineering standards, and contributing to a culture of learning.
- Be familiar with marketing data ecosystems, including GA4, advertising platforms, CRMs, and CDPs.
- Apply software engineering fundamentals, including version control, testing, code review, and CI/CD.
- Have a strong product orientation and ability to prioritize initiatives and deliver measurable business value.
- Be able to work on complex, ambiguous projects from definition through delivery.
- Have strong communication skills for working across technical levels in a 50/50 tech and creative organization.
- Have advanced English proficiency (B2 or higher).
Responsibilities
- Design, build, and scale data pipelines and infrastructure for ingestion, transformation, storage, and serving.
- Collaborate with the Machine Learning Engineering team to support model training, evaluation, and serving.
- Identify opportunities to 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, including 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.
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