NeosAlpha Technologies
Technical Architect with Data Related Skills
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Designation: Technical Architect (Modern Data Platform)
Employment Type: Full-time
Reporting To: Delivery Director / Account Director
Location: Maidenhead, United Kingdom
Job Description
We are looking for an experienced Technical Architect with deep expertise in Modern Data Platforms, Cloud Data Engineering, and Enterprise Data Architecture. The ideal candidate will be responsible for designing, architecting, and delivering scalable, secure, and high-performance data solutions that enable business intelligence, analytics, and AI-driven initiatives. This role requires a strong understanding of cloud-native data ecosystems, modern data engineering practices, and enterprise integration while collaborating closely with business stakeholders, architects, and engineering teams.
Key Responsibilities
- Design and implement enterprise-scale modern data architectures and cloud-native data platforms.
- Define end-to-end data architecture, including ingestion, transformation, storage, governance, and consumption layers.
- Strong experience in enterprise solution architecture with modern Data Engineering platforms.
- Architect scalable data pipelines for structured, semi-structured, and unstructured data.
- Lead the design and implementation of data lakes, lakehouses, and data warehouse solutions.
- Collaborate with business stakeholders to translate business requirements into scalable technical solutions.
- Establish data governance, metadata management, data quality, and security best practices.
- Drive cloud migration strategies for enterprise data platforms.
- Design real-time and batch data integration solutions using modern integration frameworks.
- Provide technical leadership and architectural guidance to engineering teams.
- Conduct architecture reviews, performance optimization, and solution validation.
- Ensure solutions comply with security, compliance, and regulatory standards.
- Mentor developers and engineers on architecture, design patterns, and modern data technologies.
- Stay updated with emerging technologies in Data Engineering, AI, Analytics, and Cloud.
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Required Skills & Qualifications
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- Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, Data Science, Computer Engineering, or a related technical discipline.
- Relevant professional certifications such as Microsoft Azure Solutions Architect, Azure Data Engineer, AWS Solutions Architect, Google Professional Cloud Architect, Databricks Certified Professional, or Snowflake Certification are highly preferred.
- 8+ years of experience in Data Engineering, Data Architecture, or Modern Data Platform solutions.
- Strong expertise in designing and implementing enterprise-scale data architectures and cloud-based data platforms.
- Hands-on experience with Data Lakes, Lakehouses, Data Warehouses, Data Modelling, ETL/ELT pipelines, and Data Governance.
- Proficiency in at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
- Experience with modern data technologies such as Databricks, Snowflake, Microsoft Fabric, Azure Synapse Analytics, Apache Spark, and Delta Lake.
- Strong programming skills in Python, SQL, and PySpark (Scala is a plus).
- Experience building scalable batch and real-time data pipelines using tools like Azure Data Factory, Apache Airflow, dbt, and Kafka.
- Good understanding of REST APIs, enterprise integration patterns, and event-driven architectures.
- Familiarity with CI/CD pipelines, Git, Azure DevOps, GitHub Actions, Jenkins, and Infrastructure as Code (Terraform preferred).
- Experience with data visualization and analytics tools such as Power BI, Tableau, or Looker.
- Knowledge of data security, metadata management, data quality frameworks, and regulatory compliance.
- Exposure to AI/ML data platforms, GenAI, Data Mesh, or Data Fabric architectures is highly desirable.
- Strong analytical, problem-solving, stakeholder management, and communication skills.
- Experience leading technical teams, mentoring engineers, and collaborating with cross-functional business and technology stakeholders.
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