Job Title: Data Architect
Below, you will find a complete breakdown of everything required of potential candidates, as well as how to apply Good luck.
Location: London - 3 days travel to office
SC Cleared: Required
Job Type: Full-Time
Experience: 10+ years
Job Summary:
We are seeking a highly experienced and visionary Data Architect to lead the design and implementation of the data architecture for our cutting-edge Azure Databricks platform focused on economic data. This platform is crucial for our Monetary Analysis, Forecasting, and Modelling efforts. The Data Architect will be responsible for defining the overall data strategy, data models, data governance framework, and data integration patterns. This role requires a deep understanding of data warehousing principles, big data technologies, cloud computing (specifically Azure), and a strong grasp of data analysis concepts within the economic domain.
Key Experience:
- Extensive Data Architecture Knowledge: They possess a deep understanding of data architecture principles, including data modeling, data warehousing, data integration, and data governance.
- Databricks Expertise: They have hands-on experience with the Databricks platform, including its various components such as Spark, Delta Lake, MLflow, and Databricks SQL. They are proficient in using Databricks for various data engineering and data science tasks.
- Cloud Platform Proficiency: They are familiar with cloud platforms like AWS, Azure, or GCP, as Databricks operates within these environments. They understand cloud-native data architectures and best practices.
- Leadership and Communication Skills: They can lead technical teams, mentor junior architects, and effectively communicate complex technical concepts to both technical and non-technical stakeholders.
Responsibilities:
Data Strategy & Vision:
- Develop and articulate the overall data strategy for the economic data platform, aligning it with business objectives and strategic themes.
- Define the target data architecture and roadmap, considering scalability, performance, security, and cost-effectiveness.
- Stay abreast of industry trends and emerging technologies in data management and analytics.
Data Modelling & Design:
- Design and implement logical and physical data models that support the analytical and modelling requirements of the platform.
- Define data dictionaries, data lineage, and metadata management processes.
- Ensure data consistency, integrity, and quality across the platform.
Data Integration & Pipelines:
- Define data integration patterns and establish robust data pipelines for ingesting, transforming, and loading data from diverse sources (e.g., APIs, databases, financial data providers).
- Work closely with data engineers to implement and optimise data pipelines within the Azure Databricks environment.
- Ensure data is readily available for modelling runtimes (Python, R, MATLAB).
Data Governance & Quality:
- Establish and enforce data governance policies, standards, and procedures.
- Define data quality metrics and implement data quality monitoring processes.
- Ensure compliance with relevant data privacy regulations and security standards.
Technology Evaluation & Selection:
- Evaluate and recommend appropriate data management technologies and tools for the platform.
- Conduct proof-of-concepts and technical evaluations to validate technology choices.
- Work with vendors and partners to ensure successful implementation of chosen technologies.
Collaboration & Communication:
- Collaborate closely with data scientists, economists, business stakeholders, and other technical teams to understand their data needs and translate them into technical solutions.
- Communicate data architecture concepts and designs effectively to both technical and non-technical audiences.
- Mentor and guide other team members on data architecture best practices.
Data Security:
- Work with security teams to ensure that data security policies and procedures are implemented and followed.
- Define data access controls and ensure that sensitive data is protected.
Qualifications and Skills:
- 10+ yearsof experience in data management, with at least5+ yearsin a Data Architect role.
- Deep understanding of data warehousing principles, data modelling techniques (e.g., dimensional modelling, data vault), and data integration patterns.
- Extensive experience with big data technologies and cloud computing, specifically Azure (minimum3+ yearshands-on experience with Azure data services).
- Strong experience with Azure Databricks, Delta Lake, and other relevant Azure services.
- Active Azure Certifications:At least one of the following is required:
- Microsoft Certified: Azure Data Engineer Associate
- Microsoft Certified: Azure Data Scientist Associate
- Active Databricks Certifications:At least one of the following is required:
- Data Engineer Associate or Professional
- ML Engineer Associate or Professional
- Experience in designing and implementing data governance frameworks and data quality processes.
- Experience working with large datasets and complex data landscapes.
- Familiarity with economic data and financial markets is highly desirable.
- Excellent communication, interpersonal, and presentation skills.
- Strong analytical and problem-solving skills.
- Experience with data visualisation tools (e.g., Tableau, Power BI).
- Experience with metadata management tools e.g. Purview.
- Knowledge of data science and machine learning concepts.
- Experience with API design and development.
