Responsibilities
- Design, implement, and maintain scalable ETL (Extract, Transform, Load) pipelines to process large volumes of data from various sources including APIs.
- Develop and optimize data warehouse architectures, ensuring data is structured and stored efficiently to meet business needs.
- Implement data validation, cleansing, and auditing processes to ensure the accuracy and reliability of data.
- Monitor and optimize the performance of data pipelines and database queries to ensure efficient data processing and retrieval.
- Maintain comprehensive documentation of data pipelines, schemas, and processes to facilitate knowledge sharing and onboarding.
- Identify, diagnose, and resolve data-related issues promptly to minimize disruptions to business operations.
- Work closely with cross-functional teams to understand data requirements and deliver data solutions that meet business objectives.
- Stay up to date with emerging technologies and best practices in data engineering and recommend improvements to existing processes.
Minimum Qualifications
- 3+ years of experience or equivalent competency building data solutions, including relational and non-relational databases, and supporting implementation and maintenance of batch and real-time data pipelines using cloud services
- Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field.
- Expertise writing simple and complex SQL queries.
- Proficiency in Python.
- Knowledge of Linux and shell scripting.
- Experience working with REST APIs to pull and push the data.
- Experience working with databases (e.g. Snowflake, Oracle).
- Understanding of data modeling, schema design, and data normalization.
- Experience with data visualization tools (e.g. Power BI).
- Ability to manage multiple tasks and priorities in a fast-paced environment.
- Self-motivated and eager to learn new technologies.
- Excellent communication and teamwork abilities.
- Strong problem-solving skills and attention to detail.
Preferred Qualifications
- Knowledge of machine learning concepts and experience working with data scientists
- Experience with AWS cloud services
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