{"id":2253812,"url":"https://alion.io/job/nttdata-senior-data-engineer-google-cloud-platform","title":"Senior Data Engineer (Google Cloud Platform)","company":{"id":4401319,"name":"NTT DATA Romania","domain":"nttdata.ro","url":"https://alion.io/company/nttdata-ro","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Iași, Romania"],"countries":["RO"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":93000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2127},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GitLab","optional":false},{"name":"GitLab CI","optional":false},{"name":"Google BigQuery","optional":false},{"name":"IAM","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-16T00:00:00Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-12T03:50:46Z","board_verified":true,"closed_at":null,"days_open":26,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":26},"description":"Who We Are\nWe are looking for an experienced Senior Google Cloud Data Engineer to join a large-scale telecommunications environment and contribute to the design, development, and operation of modern data solutions on Google Cloud Platform (GCP). In this role, you will be responsible for building scalable data platforms and processing frameworks that enable reliable data ingestion, transformation, analytics, and delivery across the organization. You will work closely with data engineers, cloud architects, DevOps teams, application teams, and business stakeholders to deliver high-quality, cloud-native solutions following engineering best practices.\nThis is a senior hands-on engineering position requiring strong technical ownership, problem-solving capabilities, and the ability to drive solutions from design through production deployment.\nWhat you'll be doing\nDesign, develop, and maintain scalable data platforms and solutions on Google Cloud Platform (GCP)\nBuild and operate batch and streaming data processing workloads using Dataflow, Dataproc, and BigQuery\nDesign and manage workflow orchestration using Apache Airflow\nImplement reliable data ingestion, transformation, storage, and delivery architectures\nOptimize data solutions for performance, scalability, reliability, and cost efficiency\nAutomate deployment processes through CI/CD pipelines, Infrastructure-as-Code, and GitLab-based DevOps practices\nMonitor, troubleshoot, and continuously improve cloud services and data processing environments\nEnsure compliance with security, governance, and operational standards\nContribute to solution architecture, technical design decisions, and code reviews\nCreate and maintain technical documentation and operational guidelines\nCollaborate with cross-functional teams in an Agile environment\nMentor junior engineers and support knowledge sharing across the engineering community\nWhat you'll bring along\nBachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience\nStrong hands-on experience with Google Cloud Platform, including Dataflow, Dataproc, BigQuery, and related cloud-native data services\nSolid understanding of data engineering architectures, ETL/ELT concepts, and large-scale distributed data processing\nExperience designing and developing batch and real-time data solutions\nStrong SQL skills and experience with data modeling and analytics workloads\nKnowledge of GCP IAM, service accounts, monitoring, observability, and troubleshooting of cloud workloads\nStrong experience with Apache Airflow, including DAG development, workflow scheduling, dependency management, and operational monitoring\nExperience with Google Cloud Composer is considered an advantage\nExperience with GitLab and GitLab CI/CD for automated build, test, and deployment workflows\nKnowledge of DevOps principles, release automation, and Infrastructure-as-Code practices\nExperience with Apache Beam, Apache Spark, or similar distributed processing frameworks is a plus\nStrong analytical, troubleshooting, and problem-solving skills\nAbility to take ownership of solutions throughout the entire lifecycle, from design to production support\nExcellent communication and stakeholder management skills within cross-functional teams\nExperience mentoring engineers and contributing to engineering best practices\nAdvanced English language skills (spoken and 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