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Business Intelligence


Tasks:
  • Develop and update a data architecture strategy that adapts to evolving needs and accommodates both Business Intelligence and AI workloads.

  • Design and implement architectures for the cloud that are vendor agnostic.

  • Design a modern scalable data platform to replace a large legacy data system in a phased approach.

  • Align architectural decisions with data governance policies and the department's vision on cloudification.

  • Establish and enforce data management policies and processes, including data quality, security and platform health monitoring.

  • Ensure regulatory compliance and adherence to audit requirements.

  • Provide guidance and mentorship to data analysts and data engineers.

  • Facilitate change management by guiding colleagues and users through the migration process.

  • Document and maintain data architecture and data assets in detail.

  • Assistance with deployment, configuration and testing of the system.

  • Participation in meetings with other project teams.

Skills Required:
  • Experience in migrating legacy data systems to a modern cloud-based, open-source data platform solution (preferably Data Lakehouse).

  • Excellent knowledge of designing scalable and flexible modern cloud-based and open-source data architectures.

  • Experience with AI-powered assistants like Amazon Q for innovative data solutions design.

  • Strong understanding of Kubernetes.

  • Knowledge of database systems, both relational (PostgreSQL, Oracle) and non-relational (Elasticsearch, MongoDB).

  • Experience with ETL/ELT processes and related data ingestion and transformation tools (like Spark, dbt, Trino).

  • Proficiency in data pipeline orchestration tools (like Airflow, Dagster, Luigi).

  • Knowledge of data governance frameworks and tools (like DataHub, Open Metadata), data quality management, data security, access control, and regulatory compliance.

  • Proficiency with system-to-system integration via RESTful APIs.

  • Experience with DevSecOps practices and tools related to data pipelines, including CI/CD for data infrastructure.

  • Excellent communication skills to articulate data architecture concepts to technical and non-technical stakeholders.

  • Good knowledge of modeling tools.

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