About Motivus

At Motivus, we believe in unlocking human potential through innovative, cutting-edge solutions. With more than 1,600 employees across five countries, we offer a full spectrum of software services and digital solutions. Our teams are dedicated to driving sustainability, pushing the boundaries of technology, and building the next generation of world-class digital solutions that empower our clients and create lasting impact.

As part of our team, you will work alongside visionary professionals committed to creating innovative solutions that shape the future of the industry.

About the Position

- We are looking for a Data Engineer with strong experience in Big Data and distributed systems to join our engineering team. In this role, you will design, develop, optimize, and support large-scale data platforms and pipelines capable of processing massive volumes of data.
- You will work primarily with real-time data pipelines, streaming analytics, distributed Big Data technologies, and data processing infrastructure, with a strong focus on scalability, performance, low latency, and fault tolerance.
- You will collaborate closely with Software Engineers, Product Managers, BI Developers, and Solution Architects to design and implement robust, scalable data solutions that support critical business and analytical needs.

Key Responsibilities

- Design, develop, implement, and optimize large-scale distributed data systems and pipelines capable of processing massive volumes of data.
- Build and maintain batch and real-time data pipelines, with a focus on scalability, low latency, performance, and fault tolerance.




- Develop data processing solutions using Java and Python.
- Design and implement streaming and distributed data processing solutions using technologies such as Kafka, Spark, Hadoop, Hive, Presto, and HBase.
- Develop and optimize complex queries across large datasets.
- Perform performance tuning and optimization of data pipelines, distributed systems, and data processing workloads.
- Design and implement MapReduce jobs and distributed data processing workflows.
- Support the implementation, operation, monitoring, and maintenance of data pipelines and analytical solutions.
- Develop and support REST API-based data services for data consumption and integration.
- Work collaboratively with engineering, product, BI, and architecture teams to deliver scalable and reliable technical solutions.
- Participate in Agile development methodologies, contributing to planning, development, testing, and continuous improvement.
- Work with cloud-based data solutions and infrastructure across GCP and/or Azure.
- Contribute to best practices around data engineering, system reliability, scalability, and operational excellence.

Required Skills & Experience

- 5+ years of professional experience in Big Data or Data Engineering.




- Strong experience designing and developing complex data pipelines and distributed data processing solutions.
- Hands-on experience with Java and/or Python for data pipelines and data processing.
- Strong proficiency in SQL, including writing and optimizing complex queries against large datasets.
- Proven experience with Big Data technologies such as:
- Hadoop
- Hive
- Kafka
- Spark
- Presto
- HBase
- Experience with Apache Airflow and Git/GitHub.
- Experience designing and implementing systems that process large volumes of data, with emphasis on scalability, performance, low latency, and fault tolerance.
- Experience developing MapReduce jobs.
- Experience with performance tuning and optimization of systems and workloads operating on large datasets.
- Experience working with cloud technologies, preferably GCP and/or Azure.
- Experience with relational databases and/or in-memory/data stores, such as Oracle, Cassandra, or Druid.
- Experience working with REST APIs for data consumption and integration.
- Experience working in Agile development environments.
- Conversational English.

Nice to Have

- Previous experience in the Retail industry.
- Experience with highly scalable, real-time or streaming data architectures.
- Experience working with Machine Learning infrastructure or data platforms supporting ML workloads.
- Experience designing solutions for petabyte-scale data environments.

Our Values

- Culture of Innovation: We foster creativity and continuous improvement.
- Responsibility: We build sustainable solutions with lasting value.
- Learning & Development: We support the growth of our people and teams.

📌 Big Data Engineer (Ciudad de México)
🏢 Motivus
📍 Ciudad de México