Data engineer Poland

Zoolatech; Región Centro; Híbrido; MXN 600.000 - 1.000.000; Jornada completa

Descripción de la vacante

Nordstrom seeks an experienced Orchestration Team Engineer to develop and maintain scalable data platforms that simplify ETL/ELT operations across diverse sources such as Kafka, S3, GCS, and BigQuery. You will collaborate with engineers, data scientists, and analysts to deliver reliable, self-service data solutions.

You will implement IaC with Terraform, orchestration with Airflow and Kubernetes, and stay ahead of evolving data governance, metadata, and lineage capabilities in a fast-moving

Formación

• Strong SQL skills and experience with BigQuery for data analysis and modeling.
• Proficient in Python and building CLIs, services, and automation.
• Experience designing and operating data pipelines (ETL/ELT) and modern transformation frameworks like dbt.
• Hands-on experience with Airflow orchestration and containerization (Kubernetes).
• Familiar with cloud data platforms (GCP, BigQuery, GCS; AWS a plus) and IaC (Terraform).
• Knowledge of data governance, metadata, data cataloging, and data lineage concepts.

Responsabilidades

• Platform development and maintenance of orchestration platforms to simplify ETL/ELT workloads for users.
• Provide production and on-call support across onsite and offshore resources.
• Provision cloud data infrastructure declaratively using Terraform.
• Develop seamless connections to data sources/destinations with high performance and reliability.
• Build and evolve metadata, cataloging, and data lineage capabilities across the data stack.
• Design scalable solutions for large data volumes and diverse formats.
• Stay current with emerging data/AI tooling to enhance framework functionality.
• Create and maintain comprehensive documentation for users and developers.

Conocimientos

SQL

Python

Data pipelines

ETL/ELT

CI/CD

GitHub Actions

Airflow

Kubernetes

Kafka

dbt

Spark

Looker/LookML

Terraform

GCP

AWS

Herramientas

BigQuery

Dataproc Serverless

GCS

Confluent Cloud

Terraform

Airflow

Kubernetes

Looker

dbt

Spark

Java/Scala

GitHub Actions

CI/CD

Descripción del empleo

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 analyzers 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.

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 to client to scale its operations while keeping technical demands on non-engineering staff to a minimum.

Platform Support: Perform ongoing production support and on‑call support duties. Work with both onsite and offshore resources daily to resolve incidents and issues.

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

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

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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