At a Glance
- Tasks: Join us as a Senior Data Architect, shaping data strategies for top-tier Telco & Utilities projects.
- Company: Be part of a leading GIS/Geo-spatial SaaS business making waves in the tech industry.
- Benefits: Enjoy flexible working options and a collaborative culture that values innovation and creativity.
- Why this job: This role offers impactful work, a chance to drive change, and develop cutting-edge data solutions.
- Qualifications: Bring your expertise in data architecture, programming, and GIS tools to the table.
- Other info: Ideal for those passionate about data and eager to make a difference in a dynamic environment.
The predicted salary is between 43200 - 72000 £ per year.
Zearch are partnering with a leading GIS/Geo-spatial SaaS business and hiring for an experienced Data Architect to work on some top priority projects in the Telco & Utilities sectors.
Data Strategy & Assessment
- Collaborate directly with clients to evaluate the technical quality and business value of their datasets, performing detailed assessments to audit critical data elements.
- Assist clients in defining processes for data governance, ensuring data accuracy, completeness, and integrity across systems.
- Conduct comprehensive reviews of client systems to understand the structure and flow of customer interaction and life-cycle data.
GIS Data Modeling & Transformation
- Design GIS data models aligned with the client’s business objectives, transforming existing data structures using tools such as Python, Perl, Safe FME, and proprietary transformation utilities.
- Translate complex datasets into standardized formats that support scalable, automated transformation workflows.
- Establish automated ingestion processes to collect and process client data, triggering transformation routines as needed.
Documentation & Compliance
- Create and maintain detailed documentation of data architectures, model configurations, and data transfer processes.
- Ensure alignment with privacy and security compliance requirements, including standards such as PII, PCI, PI, FERC, and CPNI, based on project-specific guidelines.
Deployment & Operational Support
- Serve as a key contributor on deployment teams, driving successful implementation of new data models for client-facing applications.
- Partner with client stakeholders to prioritize and select data sources based on assessment outcomes and overarching business goals.
- Ensure all data collection and transfer methods are clearly documented and meet current best practices and internal standards.
- Work closely with project managers and technical leads to integrate new enterprise data sources into ongoing projects.
ETL Development
- Develop robust, automated ETL (Extract, Transform, Load) pipelines using industry-standard tools and frameworks, prioritising scalability, reliability, and fault tolerance.
Essential Skills & Experience
- Strong background in data architecture, large-scale data modelling, and extracting business insights from raw data.
- Proficiency in data mining and manipulation, with both structured and unstructured data.
- Advanced programming skills, particularly in Python and Perl; familiarity with shell scripting and object-oriented languages (e.g., Java, JavaScript).
- Deep understanding of relational databases, data modelling principles, and entity relationship design.
- Practical experience with network design platforms and GIS/CAD tools (e.g., Smallworld, ESRI, 3GIS, Bentley, Hexagon, Crescent Link, CadTel, etc.).
- Experience with business requirement analysis and the development of reporting and analytics structures.
- Familiarity with ETL solutions, including experience with SAFE FME, is highly desirable.
- Strong knowledge of data privacy regulations and practices.
- Exposure to analytics and reporting tools is considered a plus.
General Qualifications
- Excellent communication skills, including executive presence in customer-facing roles.
- Strong interpersonal skills, with a focus on customer service and collaboration.
- Analytical mindset with exceptional attention to detail.
- Effective time manager with the ability to meet deadlines in fast-paced environments.
- Proven ability to design repeatable and automated data solutions.
- Adaptable and resilient under pressure.
Education & Background
- Bachelor’s or advanced degree in computer science, engineering, information systems, or a business/technology hybrid program (e.g., E&M, MBA).
- Significant experience in relevant technical fields may substitute for a formal IT-related degree.
Contact Detail:
Zearch Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Architect - Leading GIS/Geo-spatial Telco SaaS Business
✨Tip Number 1
Network with professionals in the GIS and Telco sectors. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and learn about the latest trends. This can help you gain insights into what companies like ours are looking for in a Senior Data Architect.
✨Tip Number 2
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, Perl, and SAFE FME. Consider working on personal projects or contributing to open-source initiatives that showcase your skills in these areas, as practical experience can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your previous experiences in data architecture and ETL development during interviews. Be ready to share specific examples of how you've designed scalable data solutions and improved data governance processes, as this will demonstrate your expertise and problem-solving abilities.
✨Tip Number 4
Stay updated on data privacy regulations and best practices, as compliance is crucial in this role. Being knowledgeable about standards like PII and PCI will not only enhance your credibility but also show that you understand the importance of data integrity and security in the GIS/Geo-spatial sector.
We think you need these skills to ace Senior Data Architect - Leading GIS/Geo-spatial Telco SaaS Business
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data architecture and GIS/Geo-spatial technologies. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your understanding of the Telco & Utilities sectors. Mention specific projects or experiences that align with the responsibilities outlined in the job description.
Showcase Technical Skills: In your application, emphasise your proficiency in Python, Perl, and ETL development. Provide examples of how you've used these skills in past projects to solve complex data challenges.
Highlight Compliance Knowledge: Demonstrate your understanding of data privacy regulations and compliance standards relevant to the role. Mention any specific experiences where you ensured data integrity and security in previous positions.
How to prepare for a job interview at Zearch
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with data architecture and GIS tools in detail. Highlight specific projects where you've designed data models or developed ETL pipelines, and be ready to explain the technologies you used, such as Python or SAFE FME.
✨Demonstrate Your Problem-Solving Skills
During the interview, expect to face scenario-based questions that assess your analytical mindset. Use examples from your past work to illustrate how you've tackled complex data challenges and contributed to successful project outcomes.
✨Communicate Clearly and Effectively
Since this role involves collaboration with clients and stakeholders, practice articulating your thoughts clearly. Focus on conveying technical concepts in a way that non-technical audiences can understand, showcasing your excellent communication skills.
✨Prepare for Compliance Discussions
Familiarise yourself with data privacy regulations relevant to the role, such as PII and PCI. Be ready to discuss how you've ensured compliance in previous projects, as this will demonstrate your understanding of the importance of data governance.