Data Engineer
Build and optimize scalable data infrastructure and ETL/ELT pipelines supporting a Search API. The role requires 3+ years of data engineering experience, Python, SQL and NoSQL expertise, AWS experience, and a quantitative bachelor's degree.
About the job
Responsibilities
- Design, build, and maintain efficient and reliable ETL/ELT pipelines for data warehousing.
- Develop and improve data infrastructure.
- Ensure data quality, integrity, and security across data platforms.
- Optimize data systems for performance and scalability.
- Troubleshoot and resolve data pipeline and data infrastructure issues.
- Collaborate with cross-functional teams to understand data needs and deliver solutions.
Requirements
- Bachelor's degree in Computer Science, Statistics, Engineering, or a related quantitative field.
- 3+ years of professional experience as a Data Engineer or in a similar data infrastructure role.
- Proficiency in Python.
- Solid experience with relational databases and SQL, as well as NoSQL databases.
- Experience with AWS and its data services.
- Experience building and optimizing data pipelines and data architectures.
Nice-to-haves
- Experience with MongoDB, Snowflake, Redis, Amazon S3 General Purpose, or Amazon S3 Express One Zone.
- Experience with big data technologies.
- Experience with Airflow.
- Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
- Experience at a company focused on API services or search technology.
- Knowledge of data governance and data security best practices.
Skills
Python, SQL, NoSQL, AWS, ETL, ELT, Data Warehousing, MongoDB, Snowflake, Redis, Amazon S3, Airflow, Docker, Kubernetes, Big Data
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