Job Description
Key Responsibilities:
Data Architecture Design:
- Design scalable and efficient data architectures that support the organization's digital platforms and applications.
- Develop logical and physical data models that represent business processes and data flows.
- Define data storage solutions, including relational databases, data lakes, data warehouses, and NoSQL databases, based on use cases and requirements.
Data Integration and Management:
- Lead the integration of data from various sources, ensuring consistency, accuracy, and timeliness.
- Implement data pipelines and ETL (Extract, Transform, Load) processes to facilitate data movement and transformation.
- Manage and optimize the performance of databases and data storage systems, ensuring low latency and high availability.
Data Governance and Security:
- Establish data governance frameworks, including data quality standards, data lineage, and metadata management.
- Define and enforce data security policies, including data encryption, access controls, and compliance with relevant regulations (e.g., GDPR, HIPAA).
- Ensure data privacy and protection measures are in place, particularly for sensitive and personally identifiable information (PII).
Collaboration and Communication:
- Work closely with business stakeholders, data scientists, data engineers, and software developers to understand data requirements and translate them into architectural solutions.
- Provide guidance on data-related issues and best practices, ensuring alignment between data architecture and business objectives.
- Document data architecture designs, data models, and processes for knowledge sharing and future reference.
Innovation and Continuous Improvement:
- Stay informed about the latest data technologies, tools, and industry trends to drive innovation in data architecture.
- Evaluate and recommend new data management technologies and platforms to improve the organization's data capabilities.
- Lead efforts to improve data architecture, including refactoring, optimization, and migration of legacy systems to modern platforms.
Data Analytics and Reporting:
- Support the development of data analytics platforms by ensuring that data architectures are designed for efficient querying and reporting.
- Collaborate with data analysts and business intelligence teams to develop dashboards, reports, and data visualizations.
- Implement data cataloging and discovery tools to enable self-service data access for business users.
Required Qualifications:
- Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.
- Extensive experience in data architecture, data modeling, and database design.
- Proficiency with data management tools and technologies, including relational databases (e.g., SQL Server, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and cloud data platforms (e.g., AWS Redshift, Azure Synapse).
- Strong understanding of data integration, ETL processes, and data warehousing concepts.
- Knowledge of data governance practices, data security standards, and regulatory compliance requirements.
- Experience with big data technologies, such as Hadoop, Spark, or Kafka.
- Familiarity with data analytics tools, such as Tableau, Power BI, or Looker.
Preferred Qualifications:
- Advanced degree (Master's or PhD) in a relevant field.
- Certifications in data management or cloud platforms (e.g., AWS Certified Big Data Specialty, Google Professional Data Engineer).
- Experience with machine learning and AI-driven data architectures.
- Knowledge of microservices and API-driven data integration.
- Proficiency in programming languages such as Python, Java, or Scala.
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