• Design, build, and maintain scalable ETL/ELT pipelines to ingest data from multiple sources including advertising platforms (Google Ads, Facebook Ads, Bing Ads), CRM systems, and operational databases • Manage and optimize our Snowflake data warehouse, including schema design, query performance tuning, and cost optimization • Configure and maintain Fivetran connectors and data integrations, ensuring data quality and timely syncs across all platforms • Develop and maintain data transformation layers using SQL and dbt to create clean, reliable datasets for analytics consumption • Build and manage automated workflows and Snowflake tasks for scheduled data refreshes and reporting • Partner with the analytics team to understand data requirements and translate them into robust technical solutions • Implement data quality monitoring, alerting, and validation frameworks to ensure accuracy and completeness • Document data models, pipelines, and processes to maintain institutional knowledge • Support HIPAA-compliant data handling practices and maintain appropriate access controls • Troubleshoot data issues and perform root cause analysis when discrepancies arise

• Analyse and maintain RDF/TTL data models and vocabularies; • Develop, optimise, and maintain SPARQL queries; • Support data ingestion, transformation, and validation workflows; • Ensure consistency and correctness of semantic data across the platform; • Collaborate with backend engineers to integrate semantic logic into application flows; • Assist in documenting semantic models, assumptions, and constraints; • Participate in troubleshooting data quality and reasoning issues.

• Build and maintain data pipelines using Azure Synapse and Spark notebooks • Perform data ingestion, transformation, and incremental loading from multiple sources • Support background processing and automation using Azure Functions • Work with relational and NoSQL databases to model and manage data • Monitor and troubleshoot data pipeline issues and performance bottlenecks

• Cloud Development: Develop and implement cloud-based backend applications and architectures. • API Integration: Build REST APIs and manage integrations with third-party service providers. • Data Pipelines: Design and deploy robust ETL/ELT pipelines using Python and Node.js. • AWS Management: Optimize data infrastructure and workflows within AWS. • Quality Assurance: Ensure high standards through rigorous testing, code versioning, and CI/CD best practices. • Continuous Improvement: Implement industry-standard tools and "value-added" best practices to enhance system performance.