Senior Data Engineer

NirYu; Estado de México; Híbrido; MXN 200,000 - 400,000; Jornada completa

Descripción de la vacante

A leading data solutions company in Mexico is looking for an experienced Data Engineer with a strong background in MLOps. The successful candidate will design and maintain scalable data infrastructures, develop APIs for data interactions, and collaborate with cross-functional teams to fulfill data needs. Key qualifications include at least 5 years of experience, proficiency in Python or Java, and familiarity with cloud services like GCP or AWS. Competitive compensation and growth opportunities are offered.

Formación

• 5+ years of experience as a Data Engineer or MLOps Engineer.
• Strong programming skills in Python, Java, or Scala.
• Experience with GCP and AWS cloud platforms.
• Hands-on with ML frameworks and deployment patterns.

Responsabilidades

• Design and maintain high-performance data infrastructure.
• Build reliable services and APIs for data interaction.
• Monitor and manage ML infrastructure and services.
• Collaborate with management and engineers in product development.

Conocimientos

Python

Java

Scala

Cloud platforms (GCP, AWS)

ML frameworks (TensorFlow, PyTorch)

Containerization (Docker, Kubernetes)

Data pipelines & ETL

Git

Excellent communication

Descripción del empleo

The Role:

We are seeking a highly motivated and experienced Data Engineer with deep expertise in MLOps discipline to join our Data Engineering team. In this role, you will be at the forefront of designing and developing scalable, robust data architectures and MLOps solutions utilizing the latest technologies from Google Cloud Platform (GCP) and AWS. As a key contributor, you will collaborate closely with cross‑functional teams to understand and address their data and ML platform requirements.

Responsibilities:

• Design, develop, and maintain scalable, high‑performance data infrastructure to support the collection, storage, and processing of large datasets in real time and batch modes.

• Build reliable, reusable services and APIs that allow teams to interact with the data platform for ingestion, transformation, and querying of data.

• Build software tools, products and systems to monitor and manage the ML infrastructure and services efficiently.

• Responsible for ensuring our ML systems are operating and running efficiently for model development, training, evaluation, and inference.

• Collaborate with senior management, product management, and other engineers in the development of data products.

• Develop tools to monitor, debug, and analyze data and ML pipelines.

• Design and implement data schemas and models that can scale.

• Mentor team members to build the company's overall expertise.

• Work to make The RealReal an innovator in the space by bringing passion and new ideas to work every day.

Requirements:

• At least 5 years of proven experience as a Data Engineer or MLOps Engineer in developing platform level capabilities for a data‑driven midsize to large corporations.

• Strong programming skills in languages such as Python, Java or Scala, with experience building large‑scale, fault‑tolerant systems.

• Experience with cloud platforms (GCP, AWS, AZURE) with strong preference to GCP.

• Experience with BigQuery or similar (Redshift, Snowflake, other MPP databases).

• Hands‑on experience with ML frameworks (TensorFlow, PyTorch) and ML deployment patterns.

• Practical experience with containerization and orchestration tools (Docker, Kubernetes).

• Experience building data pipelines & ETL.

• Experience with command line, version control software (git).

• Excellent communication and collaboration skills.

• Ability to work independently and quickly become productive after joining.

Preferred Requirements:

• Knowledge of distributed data processing frameworks such as Apache Kafka, Flink, Spark, or similar.

• Experience with DBT (Data Build Tool) and Looker.

• Knowledge of common ML deployment patterns.