The Senior Data Engineer will design and manage Kafka-based data pipelines, ensuring data quality, security, and operational reliability while collaborating with cross-functional teams.
Who We Are
Massive Rocket is a high-growth Braze & Snowflake agency that has made significant strides in connecting digital marketing teams with product and engineering units. Founded just 5 years ago, we have experienced swift growth and are now at a crucial juncture, aspiring to reach $100M in revenue. Our focus is on delivering human experiences at scale, leveraging the latest in web, mobile, cloud, data, and AI technologies. We pride ourselves on innovation and the delivery of cutting-edge digital solutions.
Every role at Massive Rocket is Entrepreneurial - Successful people at Massive Rocket will not only think about their role but understand the roles around them, their goals and contribute to the success and growth of their team, customers and partners.
What We Offer
🚀 Fast-moving environment – you will never stop learning and growing
❤️ Supportive and positive work culture with an emphasis on our values
🌍 International presence – work with team members in Europe, the US, and around the globe
🪐 100% remote forever
🧗🏼♂️ Career progression paths and opportunities for promotion/advancement
🍕 Organized team events and outings
What we’re looking for
As a Senior Data Engineer (Kafka) own our real‑time data streaming stack. Design, build, and operate Kafka-based pipelines (Confluent Cloud/self‑managed) that deliver reliable, compliant, and scalable event flows across systems. Partner with cross‑functional teams to turn business needs into event-driven solutions.
Collaborate with dynamic teams to deliver amazing solutions to our clients. Your keen insight into industry trends and best practices will keep our customer data management at the cutting edge, driving innovation and excellence.
Elevate your career with us and be a catalyst for transformative customer experiences.
Responsibilities
1) Platform & Pipelines
Architect topics, partitions, retention, and compaction; build ingestion with Kafka Connect/Debezium; implement stream processing (Kafka Streams/ksqlDB/Flink/Spark).
2) Data Quality & Governance
Enforce schemas (Schema Registry: Avro/Protobuf), validation, PII handling, GDPR/CCPA; monitoring & alerting for lag, errors, and anomalies.
3) Operations
Ensure HA, DR, and security (ACLs/RBAC, encryption); manage CI/CD, IaC (Terraform/Helm), cost/throughput tuning.
4) Collaboration
Work with Data/Analytics/Marketing/Product to define events, SLAs, and interfaces; provide best‑practice guidance and enablement.
5) Optimization & Innovation
Continuously reduce latency/cost, improve reliability, evaluate new streaming tools/patterns.
Required Skills and Qualifications:
• Data Engineering: 6+ years of experience as a Data Engineer or Data Integration Engineer.
• Kafka Expertise: 3+ years of hands-on production experience with Kafka (Confluent Platform/Cloud), including Kafka Connect, Schema Registry, and Kafka Streams/ksqlDB (or alternatives such as Flink/Spark Structured Streaming).
• Programming: Proficiency in Python, with experience in building services, tooling, and test frameworks.
• Event-Driven Systems: Strong understanding of event modeling, idempotency, DLQs, backpressure handling, and data formats (Avro, Protobuf, JSON).
• Communication & Collaboration: Excellent communication skills (English C1 level); proven experience in agency, consulting, or client-facing environments.
Preferred Qualifications:
• Cloud & Infrastructure: 2+ years working with AWS, Azure, or GCP; strong knowledge of Docker and Kubernetes; CI/CD pipelines; Git.
• Containers & Orchestration: Proficiency with Kubernetes and Docker.
• Observability & Reliability: Experience with monitoring and observability tools (Prometheus, Grafana, Datadog) and incident response processes.
• CI/CD Tools: Familiarity with GitLab for pipeline automation.
• Programming: Kotlin for Kafka Streams development (≈20% of workload).
• Data Analysis: Working knowledge of Jupyter Notebook for exploratory analysis.
• Infrastructure as Code & Operations: Experience with Terraform or CloudFormation for infrastructure setup and management.
• Data Stores: Strong understanding of relational databases and big data management practices.
• Customer Data Platforms (CDPs): Hands-on experience with mParticle.
• Tag Management: Familiarity with Tealium (a strong plus).
If you're ready to launch your career to new heights at a company fuelled by passion and innovation, we want to hear from you!
Top Skills
Avro
Confluent Cloud
Datadog
Docker
Flink
Gitlab
Grafana
Jupyter Notebook
Kafka
Kafka Connect
Kafka Streams
Ksqldb
Kubernetes
Mparticle
Prometheus
Protobuf
Python
Spark
Tealium
Terraform
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