• Develop and maintain basic Microsoft 365 (M365) Power Automate workflows to support client needs. • Assist in the creation and deployment of Power Apps to streamline business processes. • Support data analysis by generating and updating reports using the M365 Office suite, including Excel. • Troubleshoot simple workflow issues and escalate complex challenges to senior team members. • Learn and help maximize the clients customized M365 Teams environment to execute deliverables. • Participate in delivering virtual demos and training sessions for solutions developed.

• Design and evolve Sword’s streaming lakehouse — the foundation that every data consumer in the company depends on. • Build and operate distributed streaming pipelines that move data at low latency and high reliability. • Own the durable workflows that coordinate complex data movement across systems. • Shape the platform’s API surface — the interface producers and consumers use so they never need to touch infrastructure. • Drive evaluations and integrations with vendor data platforms, sitting inside the architectural trade-offs rather than just consuming the output. • Contribute to the self-service and agentic layer: interfaces designed to be consumed by humans, systems, and AI agents alike. • Partner with data engineers and analysts on contracts, governance, and lineage. • Build and maintain AI-ready data infrastructure that powers ML and AI-driven products across Sword. • Leverage AI coding assistants and LLMs to accelerate development, automate documentation, and raise code quality. • Work in a regulated environment where audit, compliance, and governance are part of every design.

• Define and evolve the internal platform toolchain across the full software development lifecycle • Build reusable abstractions, templates, and modules that standardize engineering practices • Establish onboarding and platform standards for internal teams and external vendors • Improve developer velocity, deployment frequency, and operational efficiency • Architect and own CI/CD systems for reliable, repeatable deployments • Implement progressive delivery strategies including blue/green, canary, and feature-flagged releases • Standardize build, artifact management, and deployment workflows • Embed automated quality, security, and policy controls into pipelines • Define and enforce Infrastructure as Code standards using tools such as Terraform • Build reusable infrastructure modules and environment blueprints • Ensure consistency across development, staging, and production environments • Implement policy-as-code for security, compliance, and configuration management • Embed security controls across infrastructure, pipelines, and runtime environments • Design IAM models, secrets management systems, and secure configuration practices • Integrate vulnerability scanning, supply chain protections, and compliance controls • Establish centralized observability across logs, metrics, and traces • Define SLOs, error budgets, and operational performance metrics • Build incident response tooling, runbooks, and postmortem processes • Improve system reliability, reduce incident frequency, and decrease recovery time • Extend platform capabilities to support AI workloads, inference pipelines, and model deployment • Ensure governance, cost control, and security standards apply to AI-enabled systems

• Design and implement self-service database platforms that enable provisioning, scaling, and secure operations across AWS (RDS, Aurora, DynamoDB) and other cloud-native stores. • Develop Infrastructure-as-Code solutions (Terraform, Helm, GitLab CI/CD, Kubernetes Operators) to eliminate manual database operations and improve reliability. • Establish architectural standards and best practices for service-level databases in microservices environments (Postgres, MySQL, DynamoDB, etc.). • Evaluate and guide database architecture decisions for analytical and ETL workloads, balancing performance, scalability, and cost across technologies (RDS/Aurora, BigQuery, Iceberg, and other cloud-native solutions). • Build and maintain observability frameworks (Prometheus, Grafana, Datadog, OpenSearch) to ensure database health and operational excellence at scale. • Enhance system reliability through proactive monitoring, performance tuning, automation, and documentation. • Define and drive the technical roadmap for database platform modernization aligned with broader engineering strategy. • Lead initiatives to reduce operational risk, cost, and complexity across legacy and monolithic database systems. • Guide architectural transitions from shared monolithic databases to decentralized, service-owned database models. • Partner with cross-functional stakeholders to ensure database architecture supports product scalability and business growth. • Balance innovation with operational stability to maintain high availability for mission-critical systems. • Collaborate with product and platform teams on schema design, query optimization, and database best practices. • Provide tooling, documentation, and onboarding frameworks that empower engineering teams to safely manage their own databases. • Mentor DBREs in evolving from traditional DBA practices toward platform engineering and automation-first approaches. • Participate in incident response and postmortems, driving continuous improvement across database operations. • Foster a culture of shift-left ownership, reliability engineering, and engineering excellence.