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- Wilmington, North Carolina, United States
- Wilmington, North Carolina, United States
Über
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.
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Sprachkenntnisse
- English
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