Data Architect
2 weeks ago
The Data Architect will play a key role in our organization, responsible for developing, constructing, testing, and maintaining architectures such as databases and large-scale data processing systems. They will work closely with the data scientists, data analysts, and data warehouse engineers to understand and aid in the implementation of database requirements, analyze performance, and troubleshoot any existing issues.
Key Responsibilities:- Data Pipeline Development: Design and develop reliable, scalable, and high-performance data pipelines to support data analytics and reporting requirements.
- ETL Process Implementation: Implement and maintain ETL processes to acquire, integrate, and distribute data across various platforms.
- Collaboration and Communication: Collaborate with cross-functional teams to understand data and information needs.
- Technology Expertise: Utilize Snowflake, Azure, AWS, Informatica, and DataStage to build and optimize data solutions.
- Data Quality and Integrity: Ensure data quality and integrity through the implementation of testing and validation processes.
- Data Management: Manage and manipulate large datasets for analytical purposes.
- Documentation: Develop and maintain documentation related to data processing and data flow.
- Professional Development: Stay current with emerging technologies and trends in big data, data engineering, and data processing.
- Code Review and Quality Assurance: Participate in code reviews, identify areas for improvement, and ensure best practices are followed.
- Support for Data Scientists and Analysts: Support data scientists and analysts by providing infrastructure and tools necessary for analysis.
- Education: Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
- Technical Expertise: Proven experience with Snowflake, Azure, AWS, Informatica, and DataStage.
- Programming Skills: Proficiency in SQL, Python, or Java for data manipulation and analysis.
- Data Modeling and Database Design: Strong understanding of data modeling, database design, and data warehousing principles.
- ETL Tools and Processes: Experience with ETL tools and processes.
- Data Management Tools and Governance: Knowledge of data management tools and data governance practices.
- Problem-Solving and Troubleshooting: Excellent problem-solving and troubleshooting skills.
- Communication and Collaboration: Ability to work in a fast-paced and dynamic environment, with excellent communication and collaboration skills.
- Big Data Technologies: Experience with big data technologies and platforms is a plus.
aws, big data technologies, datamodeling, informatica, data governance, datastage, sql, data, database design, python, data processing, datamanagement, database, snowflake, java, etl, azure, data engineering, data warehousing
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