
Senior Data Solutions Architect
7 days ago
The role of a Data Solutions Architect involves developing and implementing data architecture strategies for large-scale enterprise systems. This includes conceptualizing an end-to-end vision outlining the seamless flow of data through successive stages.
The Data Solutions Architect will be responsible for establishing data standards, utilizing various cloud technologies, and implementing methods and procedures for tracking data quality, completeness, redundancy, compliance, and continuous improvement.
In addition, the Data Solutions Architect will evaluate and determine governance, stewardship, and frameworks for effective data management across the enterprise.
Key Responsibilities:- Develop and articulate long-term strategic goals for data architecture vision.
- Establish data standards for enterprise systems.
- Utilize various cloud technologies, including Azure, AWS, GCP, and data platforms like Databricks and Snowflake.
- Conceptualize and create an end-to-end vision outlining the seamless flow of data through successive stages.
- Implement processes for governing the identification, collection, and utilization of corporate metadata.
- Diagnose and resolve issues related to Linux servers, networks, cluster health, job failures, and performance bottlenecks.
- Develop comprehensive strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup, disaster recovery, business continuity, and archiving.
- 8+ years of hands-on experience with various database technologies.
- 6+ years of experience with Cloud-based systems and Enterprise Data Architecture.
- Ability to travel at least 25%.
- Possess certifications in AWS, Azure, and GCP to complement extensive hands-on experience.
- Opportunity to work on large-scale data projects.
- Chance to collaborate with experienced professionals.
- Professional growth and development opportunities.
- Undergraduate or graduate degree preferred.
- Valuable 'Big 4 Management Consulting experience or exposure to multiple industries.
Security and Governance: Implement and manage security measures within the Cloudera environment, including Kerberos, Apache Ranger, and Atlas, to ensure data governance and compliance.
Automation and Scripting: Develop scripts (e.g., shell, Ansible, Python) for automating administrative tasks, deployments, and monitoring.
Performance Optimization: Tune Hadoop, Hive, and Spark jobs and configurations for optimal performance, efficiency, and resource utilization.
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