Data Architect
2 weeks ago
The Data Architect will play a crucial role in our organization, responsible for designing, developing, and maintaining our data architecture and infrastructure. They will collaborate with data scientists, analysts, and other stakeholders to ensure the efficient flow and storage of data across our systems.
Key Responsibilities:- Design and Develop Scalable Data Pipelines: Develop and maintain scalable data pipelines and ETL processes to ensure efficient data flow and storage.
- Optimize Data Models and Schemas: Develop and optimize data models and schemas to ensure data quality and integrity.
- Implement and Manage Data Storage Solutions: Implement and manage data storage solutions to ensure data reliability and efficiency.
- Ensure Data Quality and Integrity: Ensure data quality and integrity through validation and testing.
- Collaborate with Cross-Functional Teams: Collaborate with cross-functional teams to understand data requirements and identify performance and scalability issues.
- Automate Data-Related Processes: Automate data-related processes and workflows to improve efficiency and productivity.
- Monitor and Optimize Data Infrastructure: Monitor and optimize data infrastructure for reliability and efficiency.
- Stay Updated with Latest Technologies: Stay updated with the latest technologies and best practices in data engineering.
- Bachelor's Degree in Computer Science or Related Field: Bachelor's degree in Computer Science, Engineering, or related field.
- Proven Experience in Data Engineering: Proven experience in data engineering or related roles.
- Expertise in SQL and Database Management Systems: Expertise in SQL and database management systems.
- Proficiency in Programming Languages: Proficiency in programming languages such as Python, Java, or Scala.
- Experience with Big Data Technologies: Experience with big data technologies (e.g. Hadoop, Spark, Kafka).
- Strong Understanding of ETL Processes: Strong understanding of ETL processes and tools.
- Ability to Design and Optimize Data Models: Ability to design and optimize data models for performance and scalability.
- Experience with Cloud-Based Data Platforms: Experience with cloud-based data platforms (e.g. AWS, Azure, GCP).
- Knowledge of Data Warehousing Concepts: Knowledge of data warehousing concepts and techniques.
- Excellent Problem-Solving and Analytical Skills: Excellent problem-solving and analytical skills.
- Good Communication and Team Collaboration Abilities: Good communication and team collaboration abilities.
- Understanding of Data Governance and Compliance Regulations: Understanding of data governance and compliance regulations.
- Experience with DevOps Practices and Tools: Experience with DevOps practices and tools is a plus.
- Certifications in Data Engineering: Certifications in data engineering or related fields are advantageous.
sql, python, etl, big data, data modeling
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