Data Engineer

About the Role

Join a global telecommunications leader to architect, develop, and maintain scalable big data applications and pipelines. You will transform raw data into high-quality, easily queried datasets by designing efficient ETL/ELT workflows and solid data architectures to support timely business insights.

Key Responsibilities

• Create cloud-native, high-performance, and scalable big data applications.
• Extract and process data from various sources ensuring correct formats, quality standards, and timely availability for analytics.
• Develop batch and streaming data pipelines with automated testing, deployment, and rigorous data validation and cleansing to guarantee data accuracy and consistency.
• Design optimal data storage models and schemas (e.g., Iceberg, Hive) for efficient querying and scalability.
• Integrate big data applications with business systems to facilitate analytics-driven decision making.
• Implement best practices in cloud cost management, software engineering, and data governance within data platform designs.
• Collaborate with architecture teams to evolve reusable big data components to meet changing business demands.
• Research and adopt new technologies to improve the sustainability and delivery of data applications.
• Contribute to defining best practices for agile development on big data platforms.

Candidate Profile

You should have proven experience designing and deploying production-ready data pipelines using Spark, Flink, and Airflow, handling real-time and batch data streams. You understand data warehousing concepts including star and snowflake schemas, and modern table formats like Apache Iceberg for optimized data storage and querying.

Strong programming skills in Python, Scala, or Java are essential to write efficient, maintainable data processing code. Familiarity with distributed systems such as Hadoop, Hive, and Trino, and the ability to unify data from APIs, RDBMS, Kafka, and other sources is necessary.

Advanced SQL skills for complex data modeling and performance tuning using distributed SQL engines like Trino are required. Experience implementing automated data validation, lineage tracking, and data security measures (e.g., Apache Ranger) to ensure data integrity and compliance is expected.

You will collaborate closely with Data Scientists and Business Analysts to translate business needs into technical data solutions, requiring strong problem solving, documentation, and cross-team communication skills.

Qualifications and Experience

• Bachelor’s degree in Computer Engineering, Computer Science, Information Technology, or a related discipline.
• Minimum 2 years of professional experience in Data Engineering, Big Data Development, or Data Architecture, with a focus on building and deploying robust data pipelines in production environments.
• Experience in telecommunications or a similarly data-intensive sector is preferred.

Additional Information

This opportunity is with a leading international telecom company committed to connectivity as a force for good. The organization fosters an inclusive culture with diverse teams and supports employee belonging, equality, and accessibility needs throughout recruitment.

Applicants who may not meet every qualification precisely are encouraged to apply, as the company values potential and diverse backgrounds.