• Develop and optimize stored procedures, functions, and queries in large relational databases. • Maintain and improve ETL workflows and back-end data transformation jobs. • Troubleshoot data quality issues and performance bottlenecks. • Participate in schema and architecture design discussions. • Review code and provide mentorship to team members.

• Capture technical requirements and contribute to high-level and low-level design for software solutions using AWS and Azure technologies. • Write production-grade Python, and SQL code that meets high standards for maintainability, security, and observability. • Build and support complex, microservice-based, event-driven systems. • Implement testing strategies and automation across the stack. • Participate in on-call rotation and help maintain system health, performance, and reliability.

• Design and build internal platform services and shared infrastructure that hundreds of engineers depend on every day, with explicit focus on developer experience and operational ergonomics. • Architect high-throughput, latency-sensitive backend platforms capable of sustaining very high request volumes with predictable, well-bounded tail latency. • Build durable, replayable event-processing pipelines and asynchronous job execution platforms that other product teams compose to ship features faster. • Design and operate caching, rate-limiting, and request-shaping layers that protect upstream systems and enable safe scaling under bursty workloads. • Develop platform abstractions, SDKs, and paved-road libraries that codify best practices and let product teams consume capabilities without re-implementing them. • Establish robust observability, SLOs, and capacity-planning practices for platform services, raising the operational bar across the organization. • Drive multi-region, fault-tolerant, and geo-distributed designs with rigorous attention to availability, durability, and graceful degradation under failure. • Lead incident response for high-impact platform issues, conduct blameless post-mortems, and drive durable engineering improvements that prevent recurrence. • Define and enforce platform-wide standards around API design, schema evolution, deployment, and backward-compatibility guarantees. • Optimize platform performance through careful profiling, data-driven tuning, and algorithmic improvements that move the needle on throughput and cost. • Partner with infrastructure, security, and SRE teams to ensure platform services meet enterprise reliability, compliance, and security obligations. • Mentor mid-level engineers and lead architectural discussions across teams, helping the broader organization grow in distributed-systems maturity. • Produce clear technical design documents, decision records, and operational runbooks that make the platform legible to future maintainers. • Continuously evaluate emerging platform technologies, open-source projects, and architectural patterns for strategic adoption.

• Design and implement performant backend services and APIs in Go, with strong attention to concurrency, error handling, and resource management. • Build cloud-native applications using Go and Kubernetes-native libraries, applying idiomatic Go patterns, well-defined module boundaries, and operational hooks that make the resulting services easy to deploy and run. • Develop CLI tools, Kubernetes controllers, and custom operators for internal platforms, designing clear command surfaces, robust error handling, and reconciliation logic that operates safely in long-running environments. • Implement gRPC and REST APIs with appropriate observability and security. • Profile and optimize Go applications for memory, GC, and goroutine behavior, applying systematic measurement, targeted improvements, and data-driven validation to deliver quantifiable gains in throughput, latency, or resource efficiency. • Integrate with messaging systems (Kafka, NATS) and data stores (PostgreSQL, Redis, etcd). • Build comprehensive automated tests, including unit, integration, and benchmark tests. • Implement structured logging, metrics emission, and distributed tracing throughout services so that operators and on-call engineers have the signals they need to diagnose issues and reason about system behavior. • Lead code reviews and uphold engineering standards in Go projects. • Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time. • Contribute meaningfully to internal Go libraries, shared platform tooling, and reusable patterns that accelerate development across multiple engineering teams and codify hard-won best practices. • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time. • Continuously evaluate Go ecosystem evolution and contribute to internal patterns.