Technical Architect

Role Description

The Senior Data & Analytics Engineer / Technical Lead will serve as a key technical contributor for designing, implementing, and supporting scalable enterprise data and analytics solutions across AWS and/or Azure ecosystems. This role is responsible for leading hands-on engineering activities across modern cloud-native data platforms, including data ingestion, transformation, orchestration, reporting, and production support functions using technologies such as Databricks, Snowflake, SQL, Python, and PySpark.

The individual will collaborate closely with architects, business stakeholders, analysts, and engineering teams to deliver scalable, maintainable, and analytics-ready solutions while supporting DevOps, CI/CD, operational excellence, and AI-enabled data initiatives across enterprise environments.

Responsibilities and Duties

• Design and implement scalable enterprise data and analytics solutions across AWS and/or Azure ecosystems
• Act as a hands-on technical lead contributing directly to architecture, engineering, optimisation, troubleshooting, deployments, and production support activities
• Build and maintain ingestion, transformation, orchestration, integration, API, and reporting pipelines using modern cloud-native technologies, including Snowflake and Databricks
• Design scalable enterprise data models, semantic/business layers, and analytics-ready data structures for reporting and analytics platforms
• Support analytics and reporting platforms, including Tableau, Power BI, and Spotfire
• Support DevOps, CI/CD, deployment automation, release management, operational support, and environment management processes
• Manage production support activities, including monitoring, incident management, root cause analysis, performance optimisation, and issue resolution
• Support implementation of AI/ML and GenAI-enabled analytics solutions, reusable frameworks, and AI-ready data platforms
• Collaborate with architects, business stakeholders, analysts, and engineering teams to deliver scalable and maintainable solutions
• Contribute to technical standards, engineering best practices, documentation, governance, and operational excellence initiatives

Qualifications

• Bachelor’s degree in computer science/software engineering or equivalent combination of education and experience
• 8+ years of total IT experience
• 6+ years of hands-on experience designing and implementing Modern Data Platforms and Analytics solutions
• Experience working in Life Sciences, Pharma or MedTech domains
• Strong hands-on expertise in SQL, Python, PySpark, and cloud-native data engineering technologies
• Strong experience with Databricks, Snowflake, Redshift, Synapse, or similar modern data platforms
• Experience with AWS and/or Azure cloud services
• Strong ETL/ELT, orchestration, pipeline development, API integrations, and performance optimisation experience
• Experience with Airflow, Step Functions, ADF, or similar orchestration technologies
• Strong understanding of enterprise data modelling, dimensional modelling, semantic/business layer modelling, and modern data warehousing concepts
• Experience supporting enterprise reporting and dashboarding solutions using Tableau, Power BI, Spotfire, or similar platforms
• Experience with CI/CD, Git-based workflows, deployment automation, and operational support activities
• Strong troubleshooting, incident management, debugging, optimisation, and production support capabilities
• Good communication, collaboration, ownership, and technical leadership skills

Preferred Qualifications

• Experience with Terraform, DevOps, and automation frameworks
• Exposure to AI/ML, GenAI, LLMs, vector databases, or AI-enabled analytics solutions
• Familiarity with AI-ready data platforms, RAG architectures, intelligent automation, or cloud AI services