Kafka Administrator

Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction.

Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients.

Join us to challenge yourself and accomplish work that matters.

We are migrating a portfolio of Apache Kafka clusters from on-premises platforms (Cloudera and Confluent) to AWS MSK, managed through a CI/CD pipeline built on Terraform and Git Lab. We are looking for a senior, hands‑on Kafka engineer to own day‑to‑day Kafka administration across both environments, drive the migration, and coordinate closely with producer and consumer application teams to ensure a smooth, low‑risk cutover.

This is a senior individual‑contributor role for someone who has run Kafka at scale in production, is comfortable in a hybrid on‑prem/cloud world, and can act as the technical point of contact between platform and application teams.

Administer and operate Kafka clusters across Cloudera, Confluent Platform, and AWS MSK.

Manage topics, partitions, replication, retention, quotas, ACLs, and consumer groups.

Tune brokers, producers, and consumers for throughput, latency, and reliability.

Handle patching, upgrades, capacity planning, and cluster health/performance troubleshooting.

Configure and maintain security: TLS/SSL, SASL, mTLS, IAM (for MSK), RBAC/ACLs, and encryption at rest and in transit.

Plan and execute migration of clusters and workloads from on‑prem (Cloudera/Confluent) to AWS MSK.

Design cutover strategies (e.g., Mirror Maker 2 / Confluent Replicator / cluster linking) with minimal downtime and no data loss.

Validate topic parity, offsets, throughput, and data integrity pre- and post-migration.

Define rollback plans and run migration dry‑runs in lower environments.

Build and maintain Kafka/MSK infrastructure using Terraform.

Manage automated deployments and configuration through Git Lab CI/CD pipelines.

Implement Git Ops practices for topic, ACL, and cluster configuration management.

Build and maintain monitoring, alerting, and dashboards in Datadog for Kafka/MSK (broker metrics, consumer lag, partition health, JVM/GC, throughput).

Establish SLAs/SLOs and proactive alerting to reduce incidents and mean‑time‑to‑resolution.

Correlate Kafka metrics with application and infrastructure telemetry.

Serve as the primary technical liaison between the Kafka platform team and producer/consumer application teams.

Advise application teams on client configuration, serialization/schema management, partitioning strategy, idempotence, and exactly‑once/at‑least‑once semantics.

Support onboarding of new producers/consumers and troubleshoot client‑side issues (rebalancing, lag, poison messages).

Coordinate migration schedules, testing, and cutover windows with each impacted team.

5+ years in data/platform/infrastructure engineering, with 4+ years operating Apache Kafka in production.

Hands‑on administration experience with Cloudera and Confluent Platform.

Production…