Senior Data Architect
Fujitsu
- United Kingdom
- Permanent
- Full-time
- Complete understanding of available frameworks (including pros and cons for each).
- Complete understanding of which applications and systems work well together, and which do not.
- Complete understanding of best design principles for Data Lakes, Databases and Data Warehouses.
- Complete understanding of ETL/ELT Pipeline tools available (including custom pipelines, custom scripts and custom APIs).
- The ability to ensure that designs adhere to client governance rules.
- The ability to allow data scientist to extract/ingest data and allow for machine learning packages to be included in pipelines (Data Bricks, Synapse Analytics, Sagemaker).
- Knowledge of multiple visualisation tools cloud and on premise (including servers needed, installation and cost) and how they interact with different frameworks including security and access (Active Directory/Kerboros/IAM/Tickets).
- Knowledge and experience of building your data solutions in cloud-based frameworks (Azure, AWS and Google).
- Experience pulling information from using unstructured data sources such as Excel, Work Documents, text files and PDFs.
- Knowledge of open-source tools and frameworks/licenses (eg Apache, GNU, MIT)
- Full understanding of server management, firewalls, IIS, HTTP protocols, Docker, setting up VMs, operating systems, including UNIX, Linux, Solaris, and MS Windows.
- Collaborate with stakeholders to understand business requirements and translate them into scalable data architecture solutions.
- Design and implement ETL/ELT processes to efficiently extract, transform, and load data from various sources into our data warehouse or data lake.
- Establish and enforce data governance policies and procedures to ensure data quality, integrity, and security across all data assets.
- Evaluate and recommend appropriate cloud platforms (e.g., AWS, Azure, Google Cloud) based on project requirements and organizational goals.
- Architect data solutions using industry-leading frameworks and technologies, ensuring scalability, reliability, and performance.
- Lead the implementation of data pipelines and workflows, leveraging automation and orchestration tools to streamline processes.
- Provide technical leadership and mentorship to junior members of the team, fostering a culture of continuous learning and growth.
- Stay abreast of emerging trends and advancements in data architecture, cloud technologies, and programming languages, and incorporate them into our solutions where applicable.
- Collaborate with cross-functional teams, including data engineers, analysts, and software developers, to deliver integrated solutions that meet business objectives.
- Act as a subject matter expert on data architecture best practices, providing guidance and support to internal teams and clients as needed.
- Bachelor's or Master's degree in computer science, engineering, or a related field.
- Proven experience as a data architect or solutions architect, with a focus on designing and implementing complex data solutions.
- Expertise in ETL/ELT processes, including data extraction, transformation, and loading.
- Strong understanding of data governance principles and experience implementing data governance frameworks.
- Proficiency in cloud platforms such as AWS, Azure, or Google Cloud, with hands-on experience deploying and managing data solutions in a cloud environment.
- Familiarity with programming languages such as Python, Java, SQL, or Scala.
- Experience with data modeling, database design, and optimization techniques.
- Experience with visualization tools such as Power BI, QuickSight, Tableau, Qlik.
- Excellent communication and collaboration skills, with the ability to effectively interact with stakeholders at all levels of the organization.
- Strong analytical and problem-solving abilities, with a keen attention to detail.
- Certifications in relevant technologies (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect) are a plus.
- Knowledge and experience with open-source tools and implementations such as Apache Kafka, Spark, Hadoop.