Senior Data Engineer At Bluechip Technologies Limited
Bluechip Technologies Limited
full-time
Description
As part of our continued growth, we are seeking an experienced Senior Data Engineer to join our Data Services Division.
This is a permanent, client-embedded role supporting tier-1 telecom customers, where you will build, operate, and continuously enhance large-scale Apache Open-Source Lakehouse and analytics platforms.
The successful candidate will play a critical role in ensuring platform reliability, delivering new analytics use cases, and serving as a trusted technical partner to our client.
Key Responsibilities
Design, develop, test, and maintain large-scale data pipelines using Apache Kafka, Spark/PySpark, Flink, Airflow, Trino, and Apache Iceberg/Delta Lake.
Build and support Bronze, Silver, and Gold medallion-layer data pipelines processing high-volume telecom data at terabyte and petabyte scale.
Design and implement dimensional (Kimball-aligned) data models, including fact tables, dimension tables, star schemas, and slowly changing dimensions (SCDs).
Contribute to data platform architecture by defining partitioning strategies, schema evolution, and storage optimization.
Serve as the primary technical point of contact for client data engineering requirements, participating in client meetings and resolving operational issues within agreed service levels.
Translate business and analytics requirements into scalable data pipelines and reusable data products.
Monitor pipeline performance, investigate and resolve data quality issues, and implement monitoring, alerting, and observability for production environments.
Maintain architecture documentation, runbooks, data dictionaries, and technical documentation to ensure knowledge continuity and reduce key-person dependency.
Mentor junior and mid-level Data Engineers through code reviews, technical guidance, and knowledge-sharing initiatives.
Collaborate with Data Architects, BI Developers, Data Analysts, and Project Managers to deliver high-quality data solutions aligned with business objectives and project timelines.
Qualifications & Requirements
Bachelor's Degree in Computer Science, Engineering, Information Technology, or a related discipline (or equivalent practical experience).
Minimum of 6 years' professional experience in Data Engineering, including at least 3 years supporting large-scale (terabyte/petabyte) data platforms.
Proven hands-on experience with the Apache Open-Source ecosystem, including Apache Spark (PySpark), Apache Kafka, Apache Airflow, andApache Iceberg or Delta Lake.
Strong SQL expertise and practical experience designing and implementing dimensional (Kimball) data models.
Experience building and supporting Medallion Architecture (Bronze, Silver, Gold) Lakehouse solutions with robust data quality and reconcilisation processes.
Strong Python programming skills for data engineering, automation, testing, and pipeline development.
Experience working within Linux and cloud-based environments.
Experience with telecom data sources such as Call Detail Records (CDRs), OSS/BSS systems, network probe data, or similar large-scale datasets is highly desirable.
Experience with Huawei network probe data ingestion will be considered a significant advantage.
Familiarity with workflow orchestration, CI/CD pipelines, and Infrastructure-as-Code practices.
Key Competencies:
Strong client engagement and stakeholder management skills.
Excellent written and verbal communication abilities.
Demonstrated ownership mindset with strong documentation practices.
Ability to manage multiple priorities across operational support and new solution delivery.
Strong analytical, troubleshooting, and problem-solving skills.
Collaborative team player with experience mentoring junior engineers.
Reliable, dependable, and comfortable working within a client-embedded hybrid environment.