
Chief Data Architect
2 weeks ago
As a Data Engineer, you will be responsible for designing and implementing scalable data pipelines using Python, SQL, and PySpark.
Key Responsibilities:
- Design and Implement Data Pipelines: Utilize Python, SQL, and PySpark to design and implement efficient data pipelines.
- Ensure Data Quality: Collaborate with cross-functional teams to ensure high-quality data sources and integrity throughout the pipeline.
- Collaboration: Work closely with stakeholders to integrate data into business applications.
- Infrastructure Management: Maintain and optimize existing data infrastructure, including ETL processes and data warehousing solutions.
- Stay Up-to-Date: Continuously update knowledge on industry trends and emerging technologies, applying new insights to drive innovation and improvement.
Requirements:
- Programming Skills: Strong foundation in programming languages such as Python, SQL, and Bash scripting.
- Cloud-Based Platforms: Experience with cloud-based data platforms, including AWS, and containerization tools like Docker and Kubernetes.
- Data Warehousing Solutions: Familiarity with data warehousing solutions, including Redshift, Snowflake, and Databricks SQL.
- Machine Learning Libraries: Knowledge of machine learning libraries, including scikit-learn and XGBoost.
- Communication Skills: Excellent communication and collaboration skills, with experience working in fast-paced environments.
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