Senior Data Solution Architect

Job description

We are seeking a highly experienced Senior Data Solution Architect to lead the design and implementation of innovative, scalable and secure data solutions, providing strategic direction and collaborating with cross-functional teams to drive advanced data initiatives. Responsibilities • Define, develop and implement architecture for cloud-based big data analytics solutions • Provide technical leadership across multiple teams, fostering collaboration and alignment on architectural decisions • Design and oversee systems for data ingestion, processing, security, governance and quality management • Evaluate, recommend and apply best practices in data management domains such as integration, modeling, governance and BI solutions • Ensure optimal performance, scalability and cost-effectiveness for data systems • Review and validate production architecture designs and solutions to ensure alignment with business requirements • Drive adoption of cutting-edge technologies including AI/ML and Generative AI tech stacks • Lead initiatives in data management domains such as master data management, MLOps and data security • Build and maintain robust CI/CD pipelines and DevOps practices in collaboration with development teams • Stay informed about emerging data architecture trends and ensure continuous improvement of solutions Requirements • 15 to 20 years of experience in software engineering with deep expertise in data solutions • At least 2 production-grade architecture designs or solution reviews in the past 2-3 years • Knowledge of architecture patterns such as DWH, Data Lake, Lambda, Kappa, Virtualization and Data Mesh • Background in centralized, distributed, decentralized and federated data systems • Experience with at least one cloud platform: Azure, AWS, GCP or Snowflake • Practical expertise with Big Data stack including Spark, Spark Streaming, Hadoop and Hive • Capability to work with NoSQL technologies like HBase or Cassandra and orchestration tools such as Oozie, Falcon or Airflow • Strong understanding of at least 2 data management domains: Data Integration, MLOps, Generative AI, Data Governance or Data Modeling • Hands-on skills in programming with Python, R, Scala, Java or .NET for PoCs or prototypes • Proficiency in DevOps and CI/CD tools such as GitLab, GitHub, Azure DevOps and containerization with Docker or Podman • Expertise in BI and data visualization tools like Power BI or Tableau