Data platform engineer Mexico

Zoolatech; Región Centro; Hybrid; MXN 500,000 - 800,000; Full time

Job summary

Zoolatech is seeking an experienced Data Engineer to join the Orchestration Team, developing and maintaining self‑service data platforms that empower engineers, data scientists, and analysts to run ETL/ELT workflows efficiently on diverse sources such as Kafka, S3, GCS, BigQuery, and Postgres.

You will contribute to metadata governance, data lineage, and scalable architectures while working across on‑site and offshore teams, with focus on Python, SQL, Airflow, and Terraform in a cloud‑first

Qualifications

• Experience building, developing, and maintaining data platforms and self‑service data processing workflows.
• Strong SQL skills with BigQuery and data warehouse concepts.
• Proficiency in Python for CLI/services/automation.
• Hands-on with cloud data platforms (GCP preferred; AWS a plus).
• Experience with Airflow, Terraform, Kubernetes, and data pipelines.

Responsibilities

• Platform Development: evolve and maintain orchestration platforms for ETL/ELT workflows.
• Platform Support: on‑call and incident resolution with onshore/offshore teams.
• Infrastructure as Code: provision cloud data infrastructure declaratively (Terraform).
• Integration: connect to diverse data sources and destinations with high performance.
• Data Governance & Metadata: build metadata, cataloging, and data lineage capabilities.
• Scalability & Innovation: design scalable solutions and adopt new big data tooling.
• Documentation: create and maintain comprehensive framework docs.

Skills

Python

SQL (BigQuery)

Airflow

Kubernetes

Kafka

LookML / Looker

GCP

Terraform

CI/CD (GitHub Actions)

Data pipelines

Tools

Airflow

Terraform

Kubernetes

Job description

Our partner is one of the largest retail e-commerce companies in North America, serving millions of customers each year and ensuring a secure and seamless shopping experience across digital and in‑store channels.

We are looking for skilled and motivated engineer Data engineer to join the innovative team.

The Orchestration team manages platforms within Insights Delivery Technology organization and offers self‑service solutions designed to empower engineers, data scientists, and analysts to seamlessly perform ETL/ELT operations on data from diverse sources such as Kafka, S3, GCS, BigQuery, and Postgres, and write processed data back to these sources via batch or real‑time processes. Increasingly, the team also owns the metadata, governance, and data‑lineage layer that makes this data discoverable and trustworthy across the company.

As an Orchestration Team Engineer, you will play a critical role in developing and maintaining this robust platform, ensuring that users can efficiently extract actionable insights without being burdened by the complexities of big data technologies. Your work will enable the client to scale its operations while keeping technical demands on non‑engineering staff to a minimum.

• Platform Development: Evolve, design, and maintain our orchestration platforms which aim to abstract the complexities of big data technologies and simplify ETL/ELT operations for users
• Platform Support: Perform ongoing production support and on‑call support duties. Work with both onsite and offshore resources daily to resolve incidents and issues.
• Infrastructure as Code: Provision and manage cloud data infrastructure declaratively with Terraform, delivering self‑service platform capabilities through automated, version‑controlled pipelines.
• Integration: Develop seamless connectivity to diverse data sources and destinations, ensuring high performance and reliability.
• Data Governance & Metadata: Build and operate metadata, cataloging, and data‑lineage capabilities that make data across Nordstrom discoverable, trustworthy, and well‑governed — including integrations across transformation, streaming, BI, and ML platforms.
• Scalability: Design solutions that are scalable and resilient, capable of handling large data volumes, high velocity, and diverse data formats.
• Innovation: Stay up-to-date with emerging big data, ETL, and AI‑assisted tooling, incorporating them into the framework as needed to enhance functionality and user experience.
• Documentation: Create and maintain comprehensive documentation, ensuring users can easily understand and utilize the framework
• Experience building, developing, and maintaining data platforms, particularly self‑service platforms that enable engineering teams, data scientists, and analysts to configure and manage data processing workflows with minimal manual intervention.
• Proficiency in SQL (e.g., BigQuery).
• Solid understanding of ETL/ELT processes, data pipeline architecture, and modern transformation frameworks such as dbt.
• Strong programming skills in Python, with the ability to build and maintain CLIs, services, and automation.
• Experience with cloud data platforms, primarily GCP (BigQuery, Dataproc Serverless, GCS); AWS experience a plus.
• Experience with Infrastructure as Code — particularly Terraform — for provisioning and managing cloud data infrastructure.
• Experience building and orchestrating data pipelines with Airflow and Kubernetes.
• Experience with streaming / event data using Kafka (e.g., Confluent Cloud).
• Working understanding of data governance concepts — metadata management, data cataloging, and data lineage.
• Familiarity with CI/CD and Git‑based workflows (GitHub Actions) for platform and pipeline delivery.
• Proficiency with AI‑assisted developer tooling — LLMs, the Model Context Protocol (MCP), and "copilot"-style productivity tools — and a track record of using them to work more effectively.
• Excellent problem‑solving and communication skills, with the ability to work effectively in a collaborative environment.

Nice to Have

• Hands‑on experience with a metadata / data‑catalog / lineage platform such as DataHub (or Collibra, Amundsen, or similar).
• Experience with BI / semantic‑layer tools such as Looker / LookML.
• Experience with data quality, observability, SLOs / error budgets, and on‑call operations for data platforms.
• Familiarity with distributed processing frameworks such as Spark; Java / Scala a plus.

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