• 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.

• Lead pre-migration discovery sessions with public safety agencies. • Guide agencies through completion of migration questionnaires and data documentation. • Serve as the primary migration point of contact for agency stakeholders. • Clearly explain differences between legacy systems and Mark43 data structures and functionality. • Bridge gaps between how data existed historically and how it will function within Mark43. • Partner closely with the Mark43 Data Migration Engineering team to translate agency requirements into technical migration deliverables. • When applicable, collaborate with third-party migration contractors to support accurate data mapping, transformation, and execution. • Ensure alignment between customer expectations and technical implementation. • Support project planning and track migration milestones alongside project Program Managers. • Identify data risks, inconsistencies, and timeline concerns early in the process. • Facilitate structured migration validation rounds with agencies. • Track validation feedback and drive issue resolution in coordination with engineers and contractors. • Participate in user acceptance testing and quality assurance efforts. • Contribute to improving migration questionnaires, documentation, and validation workflows. • Support scalable and repeatable migration processes within Professional Services.