Senior Data Architect
hace 4 semanas
We are seeking a highly skilled Senior Data Architect to lead the development of robust data architectures, drive data governance and security standards, and ensure seamless data integration from diverse sources. The ideal candidate will have extensive experience in designing and optimizing data solutions across cloud platforms and modern database technologies.
Key Responsibilities:
- Data Modeling: Design and implement conceptual, logical, and physical data models that meet the needs of both operational and analytical use cases.
- Database Technologies: Architect data solutions using a variety of relational (SQL Server, Oracle, MySQL) and NoSQL (MongoDB, Cassandra) databases.
- Data Warehousing: Lead the design and implementation of scalable data warehouses on platforms like Snowflake, Redshift, or BigQuery to support business intelligence and reporting.
- ETL/ELT: Manage and optimize ETL/ELT pipelines using tools such as Talend, Informatica, or Apache Nifi to ensure efficient data movement and transformation.
- Cloud Platforms: Utilize cloud platforms such as AWS, Azure, or GCP to store, process, and analyze large datasets. Expertise in leveraging services like AWS S3, Azure Data Lake, and GCP BigQuery is required.
- Big Data Technologies: Work with distributed data processing technologies such as Hadoop, Spark, or Kafka to manage and process large-scale datasets.
- Data Governance & Security: Implement data governance frameworks, ensuring data quality, privacy, and compliance with regulations like GDPR and HIPAA. Apply best practices in data security, encryption, and access control.
- Data Integration: Architect and manage data integration strategies, ensuring seamless flow from diverse sources like APIs, third-party applications, and legacy systems.
- BI Tools: Collaborate with BI teams to build insightful reports and dashboards using Tableau, Power BI, Looker, or Qlik.
Analytical and Design Skills:
- Analytical Thinking: Translate complex business requirements into scalable and efficient data architectures.
- Solution Design: Create end-to-end data solutions that align with the organization's objectives.
- Problem-Solving: Lead troubleshooting efforts for data-related issues, ensuring smooth operations and data integrity.
- Performance Optimization: Continuously optimize database performance and ensure efficient data pipelines.
Leadership and Collaboration:
- Team Leadership: Lead and mentor a team of data engineers and collaborate cross-functionally with data scientists, software developers, and business stakeholders.
- Stakeholder Management: Serve as the liaison between technical teams and non-technical stakeholders, communicating data strategies and aligning on project objectives.
- Project Management: Manage data architecture projects, ensuring timely delivery and adherence to Agile or Scrum methodologies.
- Mentorship: Provide training and mentorship to junior team members, fostering growth and knowledge-sharing within the team.
Required Technical Skills:
- Data modeling expertise (conceptual, logical, and physical models)
- Strong knowledge of relational and NoSQL databases (e.g., SQL Server, MongoDB)
- Data warehousing experience with platforms like Snowflake, Redshift, or BigQuery
- Proficiency with ETL/ELT tools (e.g., Talend, Informatica, Apache Nifi)
- Familiarity with big data technologies (Hadoop, Spark, Kafka)
- Solid understanding of data governance, data security, and privacy regulations
- Experience in integrating data from multiple sources, including APIs, flat files, and legacy systems
- Familiarity with BI tools (Tableau, Power BI, Looker, Qlik)
Soft Skills:
- Excellent verbal and written communication skills
- Ability to adapt to new technologies and stay updated on industry trends
- Strong analytical thinking and problem-solving capabilities
- Leadership experience, with a proven track record in mentoring and project management
Preferred Qualifications:
- Master's degree in Computer Science, Information Systems, or a related field.
- Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure Data Engineer).
- Experience with real-time data streaming solutions.
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