Role: Azure Data Architect.

Experience: 10+ years.

Location: London.

Position: Permanent.

Job Responsibilities:

1. Collaborate with various teams/regions in driving data design, identifying architectural risks, and developing and refining data models and architecture frameworks.
2. Technical experience and knowledge in Cloud Data Warehousing, data migration, and data transformation.
3. Develop and test ETL components to high standards of data quality and performance as a hands-on development lead.
4. Familiarity with Data Lakes, Data Warehouses, MDM, BI, Dashboards, AI, and ML.
5. Design data architecture patterns and ecosystems including data stores (operational systems, data lakes, data warehouses, data marts, Cosmos DB), ingress patterns (API, streaming, ETL/ELT), and egress patterns (analytics/decision tools, BI tools).
6. Lead, consult, or oversee multiple architectural engagements.
7. Oversee and contribute to the creation and maintenance of relevant data artifacts (data lineages, source to target mappings, high-level designs, interface agreements, etc.) in compliance with enterprise-level architecture standards.
8. Experience in leading and delivering data-centric projects with a concentration on Data Quality and adherence to data standards and best practices.
9. Experience in data modeling, metadata support, development, and testing for enterprise-wide data solutions.

Must have:

1. Bachelor's degree in a technical field (Comp. Science degree preferred but not mandatory).
2. Master's degree is a plus with 6+ years of experience.
3. Expertise in Power BI.
4. Expertise in ETL, Data architecture, and Data modeling.
5. Expertise working in Relational and Big Data platforms, including MySQL, and large-scale distributed systems such as Hadoop and Spark.
6. Expertise in Data Engineering, Data Governance, Data Quality, Data Lake, Data Warehousing, and Reporting/Analytics concepts.
7. Expertise building Data pipelines, Data Lakes, and Data Warehouses in Azure using Cloud services.
8. Expertise in data analysis and writing and developing complex queries using SQL.
9. Experience in designing Big Data/Cloud Solution Designs and data models.
10. Knowledge of Pyspark, Shell scripting, SQL, Python, and some of the standard data science packages (Pandas, Numpy, etc.).
11. Strong verbal and business communication skills.
12. Experience in the manufacturing domain (add-on).