Data Engineer

Reference: DE001_1780929148

We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high-performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

  • Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud-native technologies.
  • Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.
  • Develop dimensional data models and analytics-ready datasets to support business intelligence and advanced analytics.
  • Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.
  • Build and support batch and near-real-time data pipelines using Kafka, Spark, and Airflow.
  • Optimize platform performance, scalability, and cost across data infrastructure and workloads.
  • Collaborate with cross-functional stakeholders to translate business requirements into scalable data solutions.
  • Drive CI/CD, infrastructure-as-code, and engineering best practices across the data platform.
  • Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

  • 8+ years of experience in Data Engineering or related fields.
  • Advanced SQL and Python development experience.
  • Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.
  • Experience designing dimensional models and enterprise-scale data warehouses.
  • Hands-on experience with Kafka, Spark/PySpark, and streaming data architectures.
  • Strong understanding of cloud platforms, particularly AWS.
  • Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.
  • Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

  • Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.
  • Exposure to Databricks and multi-cloud environments.
  • Background partnering with Data Science, Product, and Analytics teams.
  • Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

GCS is acting as an Employment Business in relation to this vacancy.

COMPETITIVE SALARY
Added 08/06/2026
Reference: DE001_1780929148

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