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About the role
Role Overview: As a Senior Data & Analytics Engineer / Technical Lead at Celito, you will play a crucial role in designing, implementing, and supporting scalable enterprise data and analytics solutions across AWS and/or Azure ecosystems. Your responsibilities will include leading hands-on engineering activities across modern cloud-native data platforms, collaborating with various teams, and ensuring the delivery of scalable, maintainable, and analytics-ready solutions. Key Responsibilities: - 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: - Bachelors 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 Role Overview: As a Senior Data & Analytics Engineer / Technical Lead at Celito, you will play a crucial role in designing, implementing, and supporting scalable enterprise data and analytics solutions across AWS and/or Azure ecosystems. Your responsibilities will include leading hands-on engineering activities across modern cloud-native data platforms, collaborating with various teams, and ensuring the delivery of scalable, maintainable, and analytics-ready solutions. Key Responsibilities: - 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 sol
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