Senior Data Engineer - Advertising
Truelogic · São Paulo, Brasil
Mais vagas de marketing remotas
É uma vaga remota: contratam de Brasil.
A vaga não divulga o salário.
Pedem pelo menos 5 anos de experiência.
Publicada por Truelogic e vigente desde 3 de novembro de 2026.
Descrição da vaga
ABOUT TRUELOGIC
At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.
Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.
By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.
OUR CLIENT
Our client is a global technology and creative network that brings together engineering and creative expertise in equal measure to help businesses drive innovation, digital transformation, and long-term growth. As part of a leading global marketing and communications group, the company combines strategy, design, and technology to deliver end-to-end digital experiences and solutions. Its portfolio includes partnerships with some of the world's most recognized brands across industries such as technology, finance, media, sports, and consumer goods.
JOB SUMMARY
We are seeking a hands-on Senior Data Engineer to build scalable data infrastructure to support data-driven insights and predictive and generative AI models. The Senior Data Engineer will lead technical workstreams, contribute to defining data engineering best practices, and mentor other engineers while collaborating closely with Machine Learning Engineering teams and cross-functional stakeholders to solve complex data challenges.
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 elegant, product-minded data solutions that drive measurable business value
- Integrate marketing data sources (GA4, advertising platforms, CRMs, 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
QUALIFICATIONS AND JOB REQUIREMENTS
Must have
- 5+ years of data engineering experience with a strong track record of ownership and impact, including building data pipelines and infrastructure from the ground up.
- Deep expertise in cloud data platforms, with clear, well-reasoned opinions on which work best and why
- Proficiency in Python and SQL for data processing and ETL
- Experience building and deploying data workloads in cloud environments (AWS, GCP, or Azure)
- Strong product orientation, with the ability to identify opportunities, prioritize initiatives, and deliver measurable business value
- Hands-on experience with AI-powered coding, agentic engineering, and AI-enabled workflows
- Proven experience mentoring others, establishing engineering standards, and contributing to a culture of learning
- Familiarity with marketing data ecosystems (GA4, advertising platforms, CRMs, CDPs)
- Solid software engineering fundamentals: version control, testing, code review, and CI/CD
- Strong communication skills, with the ability to work with every technical level at an organization that is 50/50 tech and creative
- Experience working in complex, ambiguous projects from definiti
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