• Work as part of a GCP implementation team from concept to operations • Provide deep technical subject matter expertise for successful deployment of Data Platform automation • Provide technical guidance, mentorship, and code-level support to the development team • Drive effective and efficient delivery, focusing on speed, identifying risks, implementing mitigation/contingency plans and test/compare competing solutions • Design and build production data engineering solutions to deliver our pipeline patterns using GCP Services • Ensure data quality, maintain profiles of data products, monitor system performance

• Develop, maintain and evolve data pipelines for ingestion, transformation and delivery of large-scale data, covering both batch and streaming processing • Design, optimize and maintain ETL/ELT processes using Apache Spark and Delta Lake, ensuring data performance, quality and reliability • Integrate data solutions with AWS services such as AWS Glue, Amazon DynamoDB, Amazon Athena, AWS Lambda and Amazon SQS • Monitor pipeline execution and health using Amazon CloudWatch, proactively identifying and resolving failures • Automate data infrastructure using AWS CloudFormation to ensure standardization, scalability and version control • Apply the Medallion architecture pattern (Bronze, Silver and Gold) for organization, governance and evolution of analytical data

• Design, build, and optimize scalable data pipelines for batch and real-time processing • Develop and maintain event-driven architectures for high-throughput systems • Ensure data reliability, performance, and low-latency processing across distributed environments • Collaborate with data scientists and application teams to enable analytics and AI use cases • Implement best practices in performance tuning, monitoring, and cost optimization

• Design and develop our Teamified AI data architecture & API using Python (Django Framework) and other relevant python libraries • Manage our RDBMs [SQL], NoSQL [MongoDb] and Vector [Pinecone] databases and conduct proper data governance & research • Collaborate with our leadership, product experts and software architect to integrate AI solutions into our Teamified Platform • Optimize AI augmentation models, context builders and prompt builders for performance, scalability, and efficiency. • Conduct research and stay up-to-date on the latest advancements in AI and data engineering.