Hire Resolve's client is looking for a Senior Data Engineer to join their team in Johannesburg, GP. The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines to support telecommunications CDR processing, real‑time data ingestion, and analytical workloads. This role requires expertise in data modeling, ETL development, stream processing, and distributed data systems. The ideal candidate will work closely with developers, DevOps, and analytics teams to transform raw network data into clean, structured, and query‑ready datasets that power dashboards, machine learning models, and business logic. The candidate will provide technical leadership, optimize data workflows for performance and reliability, and drive best practices in data engineering methodologies. Responsibilities Build ETL/ELT pipelines for ingesting, cleansing, and transforming CDRs and telecommunications logs from multiple network elements (5G/4G/3G/2G). Design and maintain real-time data flows using Kafka, Apache NiFi, and Apache Flink. Work with large‑scale distributed file systems for batch and streaming ingestion. Integrate and structure data for analytics platforms such as Apache Druid, Hudi, and Superset. Develop CI/CD pipelines for deploying data workflows and transformation logic. Ensure data quality, schema validation and compliance with retention and security policies. Monitor data pipeline health and optimize performance, throughput, and cost efficiency. Write complex and performant queries for data validation, transformation, aggregation, and analytics across relational and distributed platforms. Develop and optimize big data processing workflows in platforms such as Apache Spark, Hive, and Druid. Establish efficient issue tracking and workflow processes, enhancing productivity and collaboration across engineering teams. Implement security best practices and compliance frameworks to safeguard infrastructure, data, and applications from vulnerabilities and threats. Maintain secure role‑based access control mechanisms, encryption strategies, and identity management solutions to protect sensitive data and ensure regulatory compliance. Map data flows from source to transformation to consumption. Design and implement full‑text search and indexing solutions for querying and retrieval of structured and unstructured telecommunications data using Apache tools or similar search engines. Analyze and estimate storage requirements and strategies for large‑scale CDR datasets and real‑time data streams, ensuring optimal resource allocation and scalability across environments. Ensure data integrity and consistency across ingestion, transformation, and storage layers through validation checks, schema enforcement, and robust error‑handling mechanisms. Develop and maintain quality monitoring tools to proactively detect anomalies, missing records, or data corruption across pipelines. Perform other duties as assigned. Requirements Bachelor’s degree in Computer Engineering, Software Engineering, Computer Science, or a related field. Strong experience in building data pipelines using tools such as Apache NiFi, Kafka, Airflow, or similar. Proficiency in SQL, Python, and database administration and management (e.g., PostgreSQL, MySQL). Solid understanding of distributed data systems such as Hive, Hudi, and Spark. Experience with streaming frameworks such as Kafka Streams, Apache Flink, and Apache Beam. Familiarity with data serialization formats such as JSON. Knowledge of SFTP and secure data transfer mechanisms for ingesting remote files. Proficient with Linux environments, shell scripting, and storage systems such as Ceph. Experience with data governance, including data privacy and regulatory compliance (e.g., GDPR) and implementing access control, auditing, and data usage policies. Experience in maintaining a central inventory of data assets, managing metadata, and enabling searchable discovery across structured and unstructured datasets. Experience in data lineage tracking to map data flows, visualize, and track dependencies. Experience with OLAP systems, analytical modelling, columnar databases, and designing/querying multidimensional cubes. Strong problem‑solving skills, ability to work in a fast‑paced environment, and manage multiple projects efficiently. Strong collaboration skills, adaptability, and a commitment to continuous learning. How to Apply If you would like to apply for this role, kindly forward your CV to Gaby Turner at or you may forward your CV to #J-18808-Ljbffr