Enterprise data architect

The Enterprise Data Architect / Data Modeler is a senior technical leader responsible for defining, designing and governing the organization’s enterprise data architecture. You will ensure that data is modeled, structured and integrated across the organization to support analytics and AI / ML initiatives at scale. You will work closely with business stakeholders and technology teams to translate data requirements into robust logical and physical data models and establish enterprise-wide data standards that ensures consistency, quality and security across the group.Roles & ResponsibilitiesDesign and implement enterprise data models (conceptual, logical and physical) to support analytical, transactional and AI / ML workloads.Define and maintain data architecture standards, modeling conventions, integration patterns and best practices across the group.Lead the design and optimization of data warehouse and data lake architectures.Model and manage structured, semi-structured and unstructured data using relational and No SQL databases.Develop data integration strategies (ETL / ELT) and partner with data engineering teams to build reliable pipelines.Optimize database design for performance, partitioning, indexing, and query efficiency.Partner with data governance, security and compliance teams to implement data security, privacy, lineage, cataloging and access control frameworks.Collaborate with data scientists, BI developers and data engineers to ensure architecture enables advanced analytics, AI / ML pipelines and self-service BI.Qualifications, Experience, and SkillsQUALIFICATIONSBachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field.Master’s degree and certifications in cloud data architecture (AWS, Azure, GCP) or enterprise architecture frameworks (TOGAF, DAMA-DMBOK) are a plus.EXPERIENCE7+ years of progressive experience in data architecture, data engineering or database design.Proven experience designing enterprise-scale data models and leading architecture design.Hands-on expertise with relational databases (Postgre SQL, My SQL, SQL Server, Oracle) and No SQL technologies (Mongo DB, Cassandra, Dynamo DB, Cosmos DB).Exposure to graph databases (Neo4j, Amazon Neptune) is a plus.Experience with cloud data platforms such as Snowflake, Big Query, Redshift or Azure Synapse.Experience with ETL / ELT tools such as Informatica, Talend, dbt or Apache Ni Fi.Experience designing real-time streaming pipelines with Kafka, Spark Streaming or Flink.TECHNICAL AND INTERPERSONAL SKILLSExpert in data modeling tools (Erwin, ER / Studio, SQL Power Architect).Advanced SQL skills for schema design, optimization and performance tuning.Proficiency in Python or Scala for scripting and pipeline prototyping.Knowledge of orchestration frameworks (Apache Airflow, Luigi, Prefect).Familiarity with containerization (Docker, Kubernetes) and Dev Ops & CI / CD practices.Understanding of data governance, security and compliance frameworks.