
Data Architect
2 weeks ago
Overview:
This is a high-level position that involves designing, implementing, and maintaining large-scale data pipelines. The ideal candidate will have expertise in data engineering tools such as Spark, performance tuning, and optimization.
We are looking for an experienced professional who has hands-on experience with dbt (Data Build Tool) for data transformations and modeling. A strong background in analytics related to working with structured/unstructured datasets, building processes supporting data transformation, data structures, dimensional modeling, metadata, dependency, schema registration/evolution, and workload management is highly desirable.
The successful candidate will be able to work effectively in a team environment and contribute to the development of open-source projects. Experience with backend programming languages, big data tools, relational SQL and NoSQL databases, data pipeline and workflow management tools, cloud services, stream-processing systems, and object-oriented/object function scripting languages is also beneficial.
Key Responsibilities:
- Design, implement, and maintain scalable data pipelines using industry-leading technologies.
- Collaborate with cross-functional teams to identify business requirements and develop solutions.
- Develop and maintain high-quality software code using Agile methodologies.
- Identify areas for process improvements and implement changes to increase efficiency.
- Stay up-to-date with emerging trends and technologies in data engineering.
Requirements:
- Proficiency in Scala or Python.
- Experience with Spark and performance tuning.
- Hands-on experience with dbt (Data Build Tool).
- Strong analytical skills related to working with structured/unstructured datasets.
- Ability to work effectively in a team environment.
- Experience contributing to open-source projects.
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