T-Hub - Data Engineer

Working at T-Mobile’s T Hub will offer you a unique and highly rewarding experience on the IT market. As a leader in the telecommunications industry, T-Mobile provides a platform to hone your technical skills and empowers you to be a catalyst for innovation. You'll have the opportunity to work at the forefront of cutting-edge technologies, from 5G to IoT and AI, shaping the future of connectivity. The company fosters a diverse and inclusive workplace, encouraging collaboration among talented professionals and supporting continuous learning and development through mentorship.

• Strong experience with GCP: Dataflow, BigQuery performance features (partitioning, clustering), Pub/Sub, Dataproc, Cloud Monitoring/Logging.
• Nice to have: IAM, VPC basics, service accounts.
• Advanced Apache Beam skills: transforms, windowing/triggering, side inputs/outputs, state/timers for streaming, resource sizing and tuning on Dataflow.
• Spark: optimize joins/shuffles/partitioning, handle schema evolution, job debugging with metrics.
• Proficiency in Java: concurrency, immutability, profiling, reusable libraries, code quality and testing standards.
• Apache Flink: implement streaming pipelines.
• Airflow: build complex DAGs.
• SQL: advanced queries, performance tuning, incremental patterns, data quality checks and acceptance criteria.
• Willingness to travel at least 4 times a year.
• Proven ownership of production pipelines.

Nice to have:

• CI/CD for data (GitHub Actions/Cloud Build), Terraform for infrastructure-as-code.
• Docker/Kubernetes for job packaging (especially for Spark/Flink).
• Architect batch and streaming systems; select technologies and patterns; define standards and guardrails.
• Provide technical leadership and architecture for data platforms; drive strategy; build reusable frameworks; ensure reliability, scalability, security, and cost efficiency.
• Expert-level Java proficiency; system and API design; memory/concurrency profiling; performance-critical code; coding standards and review practices.
• Build platform components (libraries, templates, governance, quality frameworks) to accelerate teams.
• Deep Apache Beam expertise: high-throughput/low-latency pipelines; advanced state/timers; custom IOs; portability and cross-language considerations; performance debugging at runner level.
• 6+ years in data engineering with proven architectural leadership.
• Track record of delivering large-scale data systems and influencing cross-team outcomes.
• Set architectural direction, build frameworks, ensure security/compliance, drive measurable platform improvements, influence stakeholders.

• Design and implement batch and streaming pipelines; select Beam/Spark/Flink based on requirements.
• Perform data transformation operations for analytics and downstream services.
• Optimize jobs for performance and cost; implement robust testing and observability.
• Build and manage Airflow orchestration.
• Troubleshoot production issues, lead incident resolution, and drive root-cause fixes.
• Contribute to team standards, templates, and reusable libraries.
• Use Java and Apache Beam as the main programming language and library for streaming pipelines.
• Design and ship new pipelines or major refactors with measurable latency and cost improvements.
• Cooperate closely with the Data Engineering Lead for onboarding and code base understanding.
• Introduce or improve testing and observability patterns adopted by the team.