Senior Data Engineer - Digital Marketing (Mexico)

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 challenger holding company built to transform marketing through a faster, cheaper, and more accessible media mix modelling (MMM) and scenario planning solution.

Job Summary

They are looking for a skilled Data Engineer with 5–7 years of experience to join their team. The ideal candidate will have hands-on expertise in ETL pipelines, data transformations, and performance optimization, with strong problem-solving skills and the ability to communicate effectively across technical and non-technical teams.

Responsibilities

Pipeline Architecture: Design, build, and maintain scalable ETL pipelines for large-scale data processing.

Core Tech Stack: Work extensively with PySpark and Databricks to execute complex data transformations and workflows.

Optimization & Efficiency: Fine-tune data pipelines to maximize performance, scalability, and cloud cost-efficiency.

Cross-Functional Collaboration: Partner with engineering and business teams to translate requirements into high-quality data solutions.

Troubleshooting & Maintenance: Debug, resolve, and prevent complex data processing and pipeline bottlenecks.

Data Standards: Enforce best practices for data quality, governance, and system performance.

Qualifications and Job Requirements

Experience: 5–7 years of hands-on data engineering experience building production-grade solutions.

Core Technologies: Strong proficiency in PySpark and extensive hands-on experience with Databricks.

Specialized Expertise: Advanced knowledge of Databricks AutoLoader, Python, best practices, performance tuning, and compute cost optimization.

Data Architecture: Deep understanding of end-to-end ETL processes, complex data transformations, and pipeline optimization.

Core Competencies: Exceptional problem-solving skills and the ability to communicate technical concepts clearly across both technical and business teams.

What We Offer

100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.

Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.

Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.

Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.

Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.

Why You’ll Like Working Here

A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally.

Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America.

Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you're working with the best in your field.

Apply now!