AWS Datawarehouse, Data pipeline ecosystem, Data flow diagram, Data normalization and de-normalizati

This role bridges business needs, media performance, and technology by designing robust data pipelines, workflows and advanced automation solutions. You'll be part of a team that believes in doing work that matters - for people and the planet, extending this impact directly to our client's strategic objectives.\n\nWhat will you do :\nLead the development of automated data management and reporting solutions, reducing manual reporting efforts and significantly improving reporting efficiency and turnaround time.\nDevelop and maintain Python scripts to interact with various advertising platforms through API integrations (e.g., Facebook Ads, Google Ads, Programmatic Ads Platforms), enabling seamless data extraction and loading to desired platforms.\nProvide mentorship and technical guidance to team members, promoting the adoption of best practices in Python scripting, data engineering, and API integrations.\nDevelopment and maintain data quality checks and procedures, helping stakeholders overcome data issues before they impact the quality of the reporting solutions.\nMonitor automated jobs, troubleshooting data issues as-and-when they arise\nDevelop and manage interactive dashboards to deliver actionable insights for clients.\nSupport the development of strong working relationships with third-party data providers that we rely on for access to necessary data.\nWhat you’ll need :\nExceptional communication skills and can communicate effectively to both technical and non-technical stakeholders.\n4-5+ years of experience with AWS (including Redshift) and other cloud technologies\n4-5+ years of experience designing and maintaining data warehouses (e.g., Redshift, Big Query) as well as building complex ETL/ELT pipelines.\nExpertise in working with real-time and batch data pipelines, including API-based integration workflows.\nExperience in maintaining and executing data onboarding blueprints which map source and target data strategies and aggregations.\nAdvanced SQL proficiency, including concepts such as query optimization, indexing, and partitioning.\nHands-on experience with Python for data-related processes, using libraries like pandas, numpy, and frameworks like Flask.\nExperience with data monitoring, detection, troubleshooting as well as validation frameworks.\nProven track record of delivering well-designed, well-tested and performant software solutions and pipelines within an agile environment.