Consulting Engineer

Title: Consulting Engineer

Location: Multiple location

Job Description:

Role Summary

The Consulting Engineer (CE) is a customer-facing technical expert responsible for designing, building, and operating data-in-motion solutions on Confluent. Consulting Engineers focus on deep technical mastery in event streaming, working hands-on across development and operations to implement best-practice architectures, accelerate delivery, and help customers become self-sufficient on the Confluent platform.

They work tirelessly on customer engagements, learning how #oneteam truly operates while earning #customerlove by #gettingshitdone, and building the delivery “muscle memory” that underpins a long-term career in event streaming and distributed systems.

Key Responsibilities

Solution Design, Development & Operations

-        Design and implement Confluent- and Kafka-based solutions, including topics, schemas, connectors, ksqlDB/Flink jobs, and client applications.

-        Develop and review application code, automation, and integration logic to meet performance, reliability, and security requirements.

-        Configure and tune Confluent Platform/Cloud components (brokers, schemas, connectors, security, observability) for customer use cases.

-        Troubleshoot complex issues across the stack (apps, networking, storage, security, infrastructure) and drive them to resolution.

Delivery & Execution

-        Own core delivery activities for small to medium projects or workstreams within larger programs (e.g., Exploration, Foundation, Acceleration, Migration).

-        Follow and improve delivery frameworks, runbooks, and reusable assets to drive consistent, high-quality outcomes.

-        Identify delivery risks, dependencies, and technical gaps; propose mitigations and feed them into the broader engagement plan.

-        Collaborate closely with Solutions Architects and Engagement Managers on estimates, scoping assumptions, and implementation plans.

Customer Enablement & Best Practices

-        Provide hands-on enablement to customer engineers and operators via pair programming, code reviews, configuration assessments, and knowledge-transfer sessions.

-        Teach and apply Confluent best practices in areas such as topic design, schema evolution, multi-tenant controls, performance tuning, and resilience patterns.

-        Capture and share lessons learned as internal artifacts (how-to guides, examples, playbooks) that improve the PS practice at scale.

Practice Development & Community

-        Contribute to internal guilds and communities of practice, sharing patterns, tools, and improvements to PS offerings.

-        Participate in case studies, internal tech talks, or external meetups/blogs aligned to personal interests and practice priorities.

-        Support interviews, onboarding, and informal mentoring of more junior team members or partners.

Required Qualifications

-        Strong, hands-on experience with Apache Kafka and/or Confluent Platform/Cloud in real-world projects (producers/consumers, partitions, consumer groups, replication, security).

-        Proficiency in at least one modern programming language (e.g., Java, Scala, Python, C#) and associated build/test tools.

-        Solid understanding of distributed systems, data engineering, or big data technologies (e.g., Kafka, Flink/stream processing, Spark, NoSQL, or similar).

-        Demonstrated experience implementing and operating production workloads (on-prem and/or cloud), including monitoring, alerting, capacity planning, and incident response.

-        Experience in a customer-facing role (consulting, professional services, or similar) with evidence of owning deliverables and solving complex technical problems under time and stakeholder pressure.

-        Strong written and verbal communication skills, including documenting designs, explaining trade-offs, and collaborating with cross-functional teams.

Preferred Qualifications

-        Experience with public cloud platforms (AWS, Azure, Google Cloud Platform) and infrastructure-as-code or DevOps tooling (e.g., Terraform, Kubernetes, CI/CD).

-        Background integrating event streaming with downstream systems (databases, data warehouses, analytics platforms, SaaS), including performance and reliability considerations.

-        Prior work in Professional Services or Consulting, with comfort working in a billable, engagement-based model.

-        Contributions to open-source projects, meetups, blogs, or technical communities related to streaming, data engineering, or distributed systems.

Role Leveling

Within the Professional Services & Education career framework, the Consulting Engineer ladder spans multiple levels (e.g., Associate Consulting Engineer, Consulting Engineer, Senior Consulting Engineer, Staff Consulting Engineer, Principal Consulting Engineer). Expectations increase by level across:

-        Technical mastery in event streaming and adjacent technologies.

-        Delivery scope and complexity (from well-defined tasks to leading high-complexity migrations and unification programs).

-        Influence and impact (from individual contribution to cross-team leadership, practice development, and external thought leadership).

The Consulting Engineer role sits on the Service Delivery / Consulting Engineers track and is closely aligned with the Solutions Architect ladder, sharing common competencies but with a stronger emphasis on hands-on implementation and operations.