{"id":2253744,"url":"https://alion.io/job/nttdata-senior-data-engineerbq","title":"Senior Data Engineer(BQ)","company":{"id":4401319,"name":"NTT DATA Romania","domain":"nttdata.ro","url":"https://alion.io/company/nttdata-ro","size_band":null,"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":["Bucharest, Romania"],"countries":["RO"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":42000,"max_usd":108000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2127},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"BigQuery","optional":false},{"name":"Bitbucket","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google GKE","optional":false},{"name":"Looker","optional":false},{"name":"Python","optional":false},{"name":"QlikSense","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"CI/CD","optional":true},{"name":"Kubernetes","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-10T02:00:00Z","employer_posted_date":"2026-10-10","last_verified_at":"2026-10-12T00:04:35Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Who We Are\nWe seek a highly skilled Senior BigQuery Data Engineer with strong Python expertise to design and deliver high-performance data solutions within OneMIS. This pivotal role supports complex reporting functions and leads the migration of on-premise data platforms to Google Cloud Platform (GCP). You will manage large-scale financial datasets, ensuring secure, compliant, and low-latency data solutions for analytics and decision-making. This role demands technical mastery, problem-solving acumen, and a deep understanding of data best practices in the financial sector\nWhat You’ll Be Doing\nDesign, develop, and maintain scalable BigQuery data warehouse solutions (architecture, schema, data modeling) \nLead cloud-native data warehouse design and implementation to replace on-premise infrastructure\nOptimize BigQuery datasets, tables, and views for performance, cost, and governance through partitioning, clustering, query tuning, and workload management\nBuild robust data processing pipelines and workflows feeding BigQuery from diverse sources\nDevelop and maintain efficient ETL/ELT processes for large-volume financial data ingestion, transformation, and loading\nImplement comprehensive data quality checks, validation, and reconciliation processes \nUtilize and optimize core GCP services: BigQuery, Cloud Composer (Apache Airflow) for workflow orchestration, Dataflow (Apache Beam) for batch/streaming, and Cloud 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development. \nProven experience with Cloud Computing, demonstrating practical application of cloud services. \nDirect hands-on experience with core GCP services: BigQuery, Cloud Composer (Apache Airflow) for DAG development/orchestration, Dataflow (Apache Beam) for batch/streaming pipelines, and Cloud Storage\nGood understanding of data warehousing concepts, data flows, and data feeds\nExperience with Git-based source control, particularly Bitbucket\nExperience working in an agile development environment with familiar agile ceremonies\nSolid understanding of the banking and financial sector, including data types and regulatory landscapes\nAbility to work collaboratively in a dynamic environment\nNice to Have:\nExperience with other GCP services (GKE, Cloud Functions, Pub/Sub, Dataproc)\nFamiliarity with CI/CD pipelines and DevOps practices\nExperience with Infrastructure as Code (Terraform)\nKnowledge of data visualization tools (Qlik Sense, Tableau, Looker)\nUnderstanding of data 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