Are you passionate about designing data architectures that support seamless access, scalability, and security for modern applications? Do you excel at creating robust data infrastructure that empowers data-driven insights and decision-making? If you're ready to architect data solutions that are both innovative and resilient, our client has the perfect role for you. We're seeking a Data Architect (aka The Data Infrastructure Visionary) to design, build, and optimize data frameworks that support analytical needs, enable efficient data flow, and uphold data integrity.
As a Data Architect at our client, you'll work with data engineers, analysts, and business stakeholders to develop a data infrastructure that ensures data accessibility, accuracy, and security. Your role will be pivotal in setting the foundation for data management across the organization, from database design to data warehousing and integration strategies.
Key Responsibilities:
Design and Implement Data Architecture: Architect and implement a scalable, high-performance data infrastructure to support business analytics, data science, and operational reporting. You'll design data models, storage solutions, and integration strategies that meet organizational needs.Develop Data Governance and Security Policies: Create data governance frameworks and enforce data security policies to ensure data accuracy, privacy, and compliance. You'll establish data access controls and implement best practices for data quality management.Collaborate on Data Strategy and Roadmaps: Work closely with executive leadership, data engineers, and analysts to align the data architecture with the company's strategic goals. You'll define data roadmaps and plan for future scalability.Optimize Data Storage Solutions: Design and manage data warehousing solutions, such as Snowflake, BigQuery, or Redshift, to facilitate efficient data storage and retrieval. You'll ensure data systems are optimized for performance and cost-efficiency.Support Data Integration and ETL Processes: Develop and oversee ETL pipelines to ensure seamless integration of data from multiple sources. You'll ensure that data flows are consistent and accurate across platforms.Implement Advanced Analytics Frameworks: Enable advanced analytics by building architecture that supports machine learning and predictive analytics. You'll work closely with data scientists to ensure data is structured for model training and testing.Document and Maintain Data Architecture: Create comprehensive documentation of data architectures, schemas, and best practices. You'll ensure clear, up-to-date records that support scalability and team collaboration.Required Skills:
- Data Architecture Expertise: Extensive experience in designing and implementing data architectures, including data modeling, data warehousing, and data lakes.
- Cloud Data Platform Knowledge: Proficiency with cloud data services such as AWS, GCP, or Azure, and hands-on experience with cloud-native storage solutions like BigQuery, Redshift, or Azure SQL Data Warehouse.
- ETL and Data Integration: Strong understanding of ETL processes, data integration, and data transformation best practices. Familiarity with tools such as Apache NiFi, Talend, or Apache Airflow.
- Data Governance and Security: Expertise in setting up data governance frameworks, data quality standards, and data security policies. You're skilled at implementing access controls and compliance protocols.
- Communication and Collaboration: Proven ability to work cross-functionally with data engineers, analysts, and business stakeholders. You can communicate technical concepts clearly to both technical and non-technical audiences.
Educational Requirements:
- Bachelor's or Master's degree in Computer Science, Data Management, Information Technology, or a related field. Equivalent experience in data architecture and management may be considered.
- Certifications in data architecture or cloud data platforms (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate) are highly desirable.
Experience Requirements:
- 5+ years of experience in data architecture or a related field, with a track record of designing and implementing data frameworks.
- Experience in data modeling, database design, and managing large-scale data storage solutions.
- Familiarity with big data frameworks like Apache Hadoop, Spark, or Databricks is a plus.
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