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NTT DATA Logo NTT DATA · IT - Software Development

Senior BigQuery Engineer

Romania, Bucharest · Job Posted May 14, 2026
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Job Description

You will join the OneMIS stream, responsible for management, regulatory & risk reporting, and advanced analytics. Our mission includes enhancing data quality via KPIs and migrating data platforms to modern, cloud-native ecosystems. We operate in an agile environment, committed to responsible data practices. We are looking for a Senior Data Engineer to design and deliver scalable data pipelines and high performance analytical solutions using SQL/BigQuery, Spark/PySpark, and Python on Google Cloud. This role focuses on building reliable, cloud native data products that enable advanced reporting, analytics, and decision making across the organization.

Job Responsibility

  • Build scalable data pipelines: Design and deliver batch and real-time ETL/ELT pipelines across cloud environments to support analytics and reporting
  • Develop SQL and BigQuery solutions: Write and optimize advanced SQL transformations and build performant, cost‑efficient BigQuery data models
  • Develop Python workflows: Implement scalable data processing solutions using Python and PySpark, ensuring maintainable and high‑quality code
  • Design data models and ensure quality: Build robust data models and apply validation practices to maintain accuracy and reliability
  • Build cloud‑native data solutions: Use GCP services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub, and GCS to build and operate modern data platforms
  • Optimize performance and reliability: Troubleshoot complex pipeline issues and continuously improve compute, storage, and processing performance
  • Collaborate using strong engineering practices: Work with engineering, analytics, and business teams while contributing to CI/CD, code reviews, and testing standards

Requirements

  • University degree in computer science or a comparable qualification
  • At least 5 years of experience as a Data Engineer, building scalable data pipelines and working with cloud-based data ecosystems
  • Strong expertise in SQL and hands‑on experience building performant datasets in BigQuery (or similar cloud data warehouses)
  • Proven experience with Python and PySpark for scalable data processing in distributed environments
  • Solid understanding of data modeling, ELT/ETL patterns, and data quality best practices
  • Experience with Google Cloud Platform, particularly BigQuery, Dataflow, Cloud Composer, GCS, or equivalent cloud data services
  • Hands‑on experience building scalable data pipelines (batch and near real‑time) in a cloud‑native environment
  • Proficiency with version control, CI/CD pipelines, and automated testing frameworks
  • Ability to troubleshoot and optimize performance across compute, storage, and processing layers

Nice to have

  • Experience with Infrastructure as Code (Terraform, Ansible, Chef)
  • Knowledge of shell scripting
  • Experience in financial services or regulated environments

What we offer

  • Smooth integration and a supportive mentor
  • Pick your working style: choose from Remote, Hybrid or Office work opportunities
  • Different working hours to suit your needs
  • Sponsored certifications, trainings and top e-learning platforms
  • Private Health Insurance custom-made for you
  • Individual coaching sessions
  • Accredited Coaching School
  • Parties or themed events
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