Data Engineer

VOX is a visionary company led by a single founder, currently leading the way in flashcall and telecom carrier services, transforming the way businesses communicate, authenticate and connect. As a hyper-growth company, VOX achieved over 25% YoY revenue growth last year and is aiming to reach $100M+ revenue this year. VOX is looking for a team of growth-driven individuals to take the company to new heights.

VOX's cutting-edge technology and dedicated customer service team ensure that telcos and enterprises maintain secure, fast, and reliable connections while protecting their networks. VOX's promise of a hassle-free experience and superior customer support enables telcos and enterprises to focus on success. As a company, VOX focuses on solutions that monetize the assets of mobile network operators.

Joining VOX offers the opportunity to work with the industry's leading technologies and help them stay ahead and continue to innovate with a comprehensive suite of flashcall and telecom carrier services. VOX is highly committed to providing its employees with a dynamic, forward-thinking work environment, competitive compensation and benefits, vacation and time-off packages, and stock options. This is a once-in-a-lifetime opportunity for highly ambitious individuals, as VOX plans to expand its solutions portfolio and go public in the next 3-5 years.

About The Role

VOX is building a multi-tenant Customer Data Platform for mobile network operators across multiple countries. Our platform ingests billions of events from telecom traffic and transforms them into actionable insights, segmentation, and campaign activation.

As a Data Engineer on the VOX CDP team, you will work across Kafka ingestion, Spark processing, Iceberg/Nessie lake house modeling, Dremio/dbt transformations, and Kubernetes-based multi-tenant deployments.

This is a role for someone who wants to work deeply with high-volume event data and a modern, cloud-native analytics architecture.

Responsibilities

Event Ingestion & Streaming (Kafka KRaft)

• Build and maintain Kafka ingestion pipelines
• Define topic structures, partition strategies, retention policies, and consumer logic for multi-tenant setups
• Manage data contracts and schema evolution
• Develop idempotent ingestion services that land data into Iceberg tables

• Design and optimize Iceberg tables (partitioning, compaction, clustering, retention rules)
• Work with Nessie branches/tags to manage multi-environment (dev/test/prod) and multi-MNO deployments
• Implement Python/Spark loaders writing from Kafka → Iceberg
• Manage Iceberg compaction, metadata pruning, snapshot control, and performance tuning

• Develop Spark jobs (batch + micro-batch where needed) for: Cleaning and normalizing events Categorizing senders Engagement signals Identity stitching and grouping Audience enrichment and behavioral metrics
• Ensure Spark jobs scale efficiently across large volumes of event data

• Build dbt models on top of Iceberg datasets via Dremio and dbt
• Deliver telecom-specific analytical models including: Descriptive Analytics Quality/quantity audience scoring Campaign performance metrics RFU relevance scoring Cohort segmentation pipelines
• Optimise Dremio queries using reflections, column pruning, and Iceberg metadata

• Maintain Helm charts for each VOX deployment (multiple clusters)
• Build CI/CD pipelines (GitHub Actions/GitLab/Argo) for: Ingestion services Spark job deployment Kafka topic configs Dbt model updates Helm releases into customer clusters
• Automate rollouts, config updates, and monitoring installation

• Implement monitoring for ingestion lag, consumer errors, Iceberg table health, Spark jobs, and Dremio performance
• Implement custom Python-based data validation checks where needed
• Handle all PII with strict tenant isolation and encryption (Vault)
• Ensure compliant and governed data flows across all deployments.

• Work with product teams to translate telecom and marketing requirements into scalable data models
• Support analysts and ML engineers with clean, enriched datasets from Iceberg
• Collaborate with DevOps on cluster performance, scaling, and stability

• 3+ years of experience as a Data Engineer or equivalent, with documented experience in working with big datasets
• Strong Python engineering skills (must-have)
• Experience building pipelines on Apache Kafka (KRaft mode preferred)
• Strong SQL + experience with Iceberg table design and optimization
• Experience with Spark for large-scale processing
• Experience with dbt and SQL modeling on lakehouse storage
• Experience working with Dremio, Trino, or similar query engines
• Experience with Kubernetes, Helm, and Git-based CI/CD
• Understanding of PII handling, encryption, and compliance requirements
• Ability to work in distributed, multi-environment setups (dev/test/prod + multi-deployments)

• Experience with telecom data structures (CDRs)
• Experience with Nessie catalogs (branching, tagging, schema versioning)
• Understanding of audience-building, scoring, or marketing activation models
• Experience tuning object storage (S3/MinIO)