Data Architect

• Define and maintain enterprise data architecture, including conceptual, logical, and physical data models.
• Design scalable cloud-based data platforms, data warehouses, and data lake solutions to support business intelligence, analytics, and AI initiatives.
• Lead the design and implementation of data integration, ETL/ELT, streaming, and batch processing solutions.
• Partner with business stakeholders, product managers, architects, and engineering teams to translate business requirements into scalable technical solutions.
• Ensure data platforms are reliable, performant, secure, and highly available through monitoring, automation, and operational best practices.
• Evaluate emerging technologies and recommend improvements to modernize the enterprise data ecosystem.
• Collaborate with cross-functional teams to support AI/ML, advanced analytics, and enterprise reporting initiatives.

For applications and inquiries, contact:hirings@openkyber.com

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 10+ years of experience in data architecture, data engineering, or enterprise data platform development.
• 5+ years of experience leading data engineering projects and delivering enterprise-scale data solutions.
• Strong expertise in data modeling, data warehousing, ETL/ELT, and cloud-based data platforms.
• Experience designing distributed, scalable, and high-performance data architectures.
• Strong understanding of Agile development methodologies, CI/CD, and DevOps practices.
• Excellent communication, stakeholder management, and leadership skills.

Preferred Technical Skills

• Cloud & Data Platforms: AWS, Snowflake, S3, EMR, Glue, Redshift
• Data Engineering: Spark, Kafka, Airflow, Talend, dbt, Python, SQL
• Databases: SQL Server, PostgreSQL, Aurora, DynamoDB
• Architecture: Data Lake/Lakehouse, Event-Driven Architecture, Microservices, REST APIs, Data Modeling
• DevOps: Kubernetes, Docker, Git, CI/CD, Infrastructure as Code