Data Architect

pbEmployment Type: /b Full-time /ph3Nature of the Tasks /h3ulliDevelop and implement the organization's overarching data strategy, creating blueprints for data management that align with and enable key business objectives. /liliTranslate business requirements into technical specifications and data architecture designs, ensuring the data infrastructure supports both immediate and long-term needs. /liliCreate conceptual, logical, and physical data models (e.g., dimensional for analytics) that define data structure, relationships, and storage. /liliMaintain metadata repositories to ensure data accuracy, lineage, and integration, curating both technical and business metadata for clarity. /liliArchitect solutions to integrate data from disparate sources (ERPs, CRMs) using ETL/ELT processes and tools (e.g., Apache NiFi, Talend) into a unified framework. /liliBuild and manage streaming data pipelines (e.g., using Kafka, Spark Streaming) to support real-time analytics and decision-making. /liliDefine and enforce data governance policies, including data quality standards, lineage tracking, access controls, and a data catalog. /liliImplement security protocols (encryption, RBAC) and design architectures to ensure adherence to regulations like GDPR. /liliImplement processes for data profiling, validation, and cleansing to ensure ongoing data accuracy, consistency, and reliability. /liliEvaluate and select appropriate database systems (SQL, NoSQL), cloud platforms (AWS, Azure, GCP), and tools that meet scalability and performance needs. /liliArchitect and deploy scalable data solutions in cloud (e.g., Snowflake) or hybrid environments, optimizing for cost-efficiency. /liliMonitor, troubleshoot, and optimize data systems and pipelines for performance, scalability, and cost. /liliWork with business leaders, data engineers, and scientists to ensure the architecture meets diverse needs and bridges technical and non-technical gaps. /liliMentor data teams on best practices, standards, and tools; lead data-centric projects and strategic initiatives. /liliOversee the entire data lifecycle, from collection and storage to archiving and purging, ensuring data remains manageable and relevant. /liliStay abreast of trends in big data, AI, and cloud computing to continuously innovate and modernize the data architecture. /li /ulh3Specific Expertise and Technologies /h3ulliKnowledge of enterprise data architecture methods and reference models (e.g., DAMA-DMBOK, Data Mesh principles, Data Fabric patterns). /liliKnowledge of data modelling approaches: 3NF, dimensional/star-schema, and Data Vault 2.0; experience with modelling languages/tools (e.g., ER, UML, ArchiMate; ERwin, SAP PowerDesigner). /liliExperience with metadata and cataloguing platforms to govern lineage and ownership (e.g., Collibra, Alation, Azure Purview, OpenLineage). /liliKnowledge of data governance and quality frameworks (e.g., ISO 8000, ISO/IEC 11179), including stewardship, data domains, and controls. /liliUnderstanding of privacy, security, and compliance requirements (e.g., GDPR, ISO/IEC 27001), including encryption, key management, RBAC/ABAC, and data residency. /liliExperience with integration patterns and pipelines: ETL/ELT, CDC, event streaming (e.g., Kafka, Debezium) and orchestration (e.g., Airflow, Azure Data Factory, Dagster). /liliKnowledge of lakehouse and warehouse architectures, table/format standards (e.g., Delta Lake, Apache Iceberg, Apache Hudi) and columnar formats (e.g., Parquet). /liliExperience with cloud data platforms such as Azure Synapse, Databricks, Microsoft Fabric, Snowflake, and Amazon Redshift. /liliKnowledge of relational and NoSQL data stores and when to apply them (e.g., PostgreSQL, Oracle, MongoDB, Cassandra, time-series and graph databases). /liliExperience with distributed compute/query engines (e.g., Spark, Trino/Presto, Databricks SQL) for large-scale processing. /liliKnowledge of API and interoperability standards for data access (e.g., SQL, REST, GraphQL, gRPC, OpenAPI/AsyncAPI specifications). /liliExperience with semantic/metrics layers and BI modelling (e.g., dbt Semantic Layer, LookML, MetricFlow) to standardize KPIs. /liliUnderstanding of master and reference data management practices and tooling (e.g., Informatica MDM, Semarchy, Reltio). /liliExperience with data quality/observability tooling and SLAs/SLOs (e.g., Great Expectations, Soda, Monte Carlo) to monitor freshness, completeness, and lineage. /liliKnowledge of streaming and real-time patterns (e.g., Spark Structured Streaming, Flink) and state stores (e.g., Kafka Streams). /liliExperience with DevSecOps/DataOps practices: version control, CI/CD for data, automated testing, and environment promotion (e.g., Git, GitHub/GitLab CI). /liliKnowledge of Infrastructure-as-Code and Policy-as-Code for data platforms (e.g., Terraform, Bicep, OPA) to ensure repeatable, governed deployments. /liliUnderstanding of backup/restore, disaster recovery, and retention strategies with