Engineering Lead

Job Description

Strategic Imperative:

The Engineering Lead is the technical multiplier for the team—owning the most complex and distributed-system deliverables while shaping how engineering work is designed, implemented, and operated at scale. This role translates platform strategy into durable architecture and production outcomes, raising the bar for reliability, security, performance, and maintainability across services, data, and event-driven workflows. Beyond hands-on delivery, the Engineering Lead drives technical alignment through design leadership, standards, and mentorship—reducing long-term technical risk, accelerating iteration, and enabling teams and systems to scale sustainably.

Prodege

A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Great Hill Partners in Q4 2021 and strategic acquisitions of Pollfish, BitBurst & AdGate Media in 2022, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.

As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today!

Primary Objectives

• Lead delivery of high-impact technical outcomes: Own and deliver complex initiatives across services, data, and integrations—ensuring quality, scalability, and predictable execution.
• Advance architecture and platform direction: Influence system design, microservices evolution, and event-driven architecture through strong technical judgment, design reviews, and clear architecture artifacts.
• Strengthen reliability and operational excellence: Improve observability, incident readiness, and system resilience by driving durable fixes, reliability enhancements, and runbook maturity.
• Raise engineering standards and reduce technical risk: Model and enforce best practices in secure coding, privacy/compliance, testing discipline, code review rigor, and clean API/service contracts.
• Optimize performance and scalability at enterprise scale: Identify bottlenecks and implement tuning across application, service, streaming, and database layers (profiling, caching, SQL optimization, concurrency).
• Accelerate delivery through tooling and automation: Improve CI/CD, deployment safety, and developer workflows to increase velocity while protecting stability and release quality.
• Enable team capability and technical leadership: Mentor engineers, unblock complex problems, and drive cross-functional alignment with Product, QA, DevOps, and Infrastructure to deliver cohesive
  
  

• Own end-to-end delivery of complex systems/features by leading requirements refinement, technical design, implementation, testing strategy, rollout, and long-term maintenance for critical services.
• Drive architectural direction for the team by proposing and deciding on scalable, resilient designs (e.g., microservices boundaries, event-driven patterns, CQRS) and ensuring solutions align with long-term platform strategy.
• Design and build distributed, high-availability services including service-to-service contracts, communication patterns (Kafka/RabbitMQ/gRPC), reliability mechanisms, and safe failure handling.
• Lead API design and governance by creating versioned, backward-compatible APIs, setting contract standards, and enforcing validation, authentication/authorization, and rate-limiting practices.
• Ensure scalability and performance through proactive profiling, JVM tuning (GC, memory, concurrency), load testing, capacity planning, and optimization for high-traffic/large-scale environments.
• Own production operational excellence by defining SLIs/SLOs, improving monitoring/alerting, participating in on-call and incident response, running root-cause analyses, and driving post-incident remediation to prevent recurrence.
• Solve the hardest technical problems by acting as the escalation point for debugging complex issues (performance bottlenecks, memory leaks, race conditions, distributed tracing challenges) across pre-prod and production.
• Engineer data storage and caching solutions by selecting appropriate database technologies (MySQL/Redis/Mongo), designing schemas/data models, defining indexing/partitioning strategies, and tuning queries for large datasets.
• Embed security and compliance by design by implementing encryption, key management, OAuth flows, secure coding practices, and threat-aware architecture reviews for owned systems.
• Set and enforce code quality standards via deep code reviews, establishing testing expectations (unit/integration/contract), improving maintainability, and reducing technical debt in critical areas.
• Mentor and coach software engineers and senior software engineers by guiding design choices, helping unblock implementation, reviewing technical documents, and supporting career growth through regular feedback and development plans.
• Lead technical planning and execution by breaking down ambiguous problems, defining milestones, identifying risks/dependencies early, and ensuring delivery meets quality, timeline, and reliability expectations.
• Collaborate with cross-functional stakeholders (PM, QA, SRE/DevOps, Security, other teams) to align on scope, tradeoffs, and integration plans while influencing decisions through clear technical communication.
• Drive process and tooling improvements by introducing or enhancing CI/CD pipelines, automation, development workflows, coding standards, and internal documentation/playbooks.
• Continuously modernize systems by identifying areas for refactoring, migration, or re-architecture, evaluating new technologies, and executing improvements that increase team velocity and system robustness.
• Build deep product/domain expertise and proactively propose enhancements that improve user outcomes, reduce operational cost, and increase engineering efficiency.
  
  

• Bachelor’s degree (or equivalent) in Computer Science, Software Engineering, Information Technology, or a related discipline.
• Seven or more (7+) years of experience in software engineering with deep backend/distributed systems ownership (full-stack backgrounds acceptable).
• Mastery of advanced Java concepts, including concurrency, memory management, JVM internals, and garbage collection tuning. Capable of optimizing Java applications for performance and scalability in high-traffic environments
• Deep understanding of system architecture principles, ability to design large-scale, distributed systems with a focus on scalability, reliability, and performance. Proficiency in applying advanced design patterns (e.g., Dependency Injection, Event-Driven Architecture, CQRS).
• Extensive experience designing, implementing, and maintaining microservices-based architectures, ensuring loose coupling, high availability, and efficient communication across services using technologies such as Kafka, RabbitMQ, or gRPC
• Strong expertise in relational and non-relational databases (e.g., MySQL, Redis, Mongo), including advanced data modeling, partitioning, indexing strategies, and optimizing performance for large datasets.
• Usage of AI (Github Copilot/Claude Code, etc.)
• Ability to diagnose and resolve complex system-level issues, including performance bottlenecks, memory leaks, and concurrency challenges in both production and pre-production environments.
• Thorough knowledge of advanced security principles, including encryption, key management, OAuth, and secure application design.
• Experience designing versioned APIs, implementing API gateways, and ensuring backward compatibility. Experience implementing security measures such as rate limiting, API authentication, and request validation
• Ability to guide and mentor software and senior software engineers in producing high-quality code, performing in-depth code reviews, and promoting best practices in code maintainability, testing, and scalability
• Ability to apply AI and machine learning tools responsibly in support of predictive modeling, analysis, experimentation, and solution development, including validating outputs, documenting assumptions, and adhering to company security and confidentiality standards.
• Strong analytical and troubleshooting skills with the ability to resolve complex infrastructure issues.
• Excellent verbal and written communication skills, with the ability to convey technical information clearly to both technical and non-technical stakeholders.
  
  

• Experience with large-scale distributed systems
• Knowledge of event sourcing and CQRS patterns
• Exposure to frontend frameworks (React, Angular, Vue)
• Experience with Infrastructure as Code (Terraform or equivalent)
• Familiarity with observability platforms (Prometheus, Grafana, ELK stack)
• Experience working in regulated or enterprise compliance environments
• Prior experience in mentoring or technical leadership roles