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Data Engineer
Posted: 10/25/2024
Job Number: z5G7h3l6a1kMvyS65NP3cyDDAN2OdRKzq3960oQh8ts=
Pay Rate: 40-55 Hourly USD
Job Description
Responsibilities:
- Data Pipeline Development: Design, build, and maintain scalable ETL pipelines to ensure efficient data flow from diverse sources into data warehouses.
- Workflow Automation: Utilize Apache Airflow for scheduling and managing complex data workflows.
- Collaboration: Partner with data scientists to implement machine learning models (MLOps) in production.
- Coding and Scripting: Write high-quality Python code for data extraction, transformation, and loading tasks.
- Big Data Processing: Use Databricks for processing large datasets and optimizing data workflows.
- Data Quality Management: Ensure data accuracy and integrity by implementing monitoring, logging, and alerting mechanisms.
- Version Control: Use GitHub for code management and collaboration, maintaining clear documentation of data processes.
- Database Management: Work with Snowflake and BigQuery for data storage and analytics, ensuring optimal performance and scalability.
- Performance Optimization: Analyze and tune data storage solutions and SQL queries for efficiency.
- Cross-Functional Support: Collaborate with business units to identify and fulfill data needs effectively.
Basic Qualifications:
- 3+ years of experience in data engineering or a related field.
- Proficient in Python for data processing and scripting.
- Experience with Apache Airflow or similar workflow management tools.
- Familiarity with machine learning operations (MLOps) and model deployment.
- Solid understanding of cloud platforms (AWS, Azure, GCP).
- Strong SQL skills and experience with data modeling.
- Practical experience with Snowflake and BigQuery.
Preferred Skills:
- Knowledge of Databricks for data processing and analytics.
- Experience with data visualization tools like Tableau or Power BI.
- Familiarity with containerization technologies such as Docker.
- Understanding of DataOps principles and practices.
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