Data Architect
4 weeks ago
We are seeking a highly skilled Data Architect to design, optimize, and manage our enterprise data architecture. The role involves defining how data is collected, stored, accessed, and leveraged across the organization, ensuring scalability, security, and performance. You will collaborate with stakeholders, engineers, and analysts to establish robust data models and frameworks that drive business intelligence and advanced analytics.
Key Responsibilities
- Design, implement, and maintain the overall data architecture (data models, standards, and guidelines).
- Develop and optimize data pipelines, ETL/ELT processes, and integration frameworks for structured and unstructured data.
- Define and enforce data governance, security, and compliance policies (GDPR, HIPAA, etc. as applicable).
- Collaborate with data engineers, BI developers, and analysts to ensure data availability and usability.
- Evaluate and recommend data storage solutions (data lakes, data warehouses, cloud platforms).
- Define metadata management, master data management (MDM), and data lineage strategies.
- Establish performance tuning and cost optimization practices for large-scale data environments.
- Provide technical leadership in cloud data platforms (AWS, Azure, GCP) and emerging technologies.
- Translate business requirements into scalable data solutions that support analytics, AI/ML, and reporting.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
- Proven experience (9+ years) as a Data Architect, Data Engineer, or Database Architect.
- Strong knowledge of data modeling (conceptual, logical, physical) and database design.
- Expertise in SQL/NoSQL databases (e.g., Oracle, MySQL, PostgreSQL, MongoDB, Cassandra).
- Hands-on experience with data integration tools (Informatica, Talend, Apache Nifi, dbt).
- Proficiency with cloud data platforms (AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake).
- Familiarity with big data frameworks (Hadoop, Spark, Kafka) and real-time streaming data.
- Strong understanding of data security, compliance, and governance frameworks.
- Excellent communication and stakeholder management skills.
Preferred Qualifications
- Experience with containerization & orchestration (Docker, Kubernetes).
- Knowledge of AI/ML pipelines and data science workflows.
- Certifications in cloud platforms (AWS Certified Data Analytics, Google Professional Data Engineer, Azure Data Engineer Associate).
- Experience in designing data mesh / data fabric architectures.
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