{"id":3107493,"url":"https://alion.io/job/deutsche-telekom-digital-labs-data-architect-gcp-2","title":"Data Architect - GCP","company":{"id":409,"name":"Deutsche Telekom Digital Labs","domain":"dtdl.in","url":"https://alion.io/company/deutsche-telekom-digital-labs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":57000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Alation","optional":false},{"name":"Apache Kafka","optional":false},{"name":"CI/CD","optional":false},{"name":"Collibra","optional":false},{"name":"Data Vault","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Google GKE","optional":false},{"name":"IAM","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-22T19:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-22T19:35:00Z","board_verified":false,"closed_at":null,"days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"We are looking for an experienced GCP Data Architect to lead the design and implementation of enterprise-scale data platforms on Google Cloud Platform (GCP). This is a strategic role responsible for defining the organisation's data architecture, enabling modern analytics, and building scalable, secure, and high-performance data solutions.\n\nThe ideal candidate will have strong expertise in GCP data services, data architecture, data engineering, cloud-native technologies, and enterprise data governance. You will work closely with product, engineering, analytics, and business teams to build reliable data platforms that support reporting, analytics, and future AI/ML initiatives.\n\nThe core responsibilities for the job include the following:\n\nData Architecture: \nDesign and maintain enterprise-wide data architecture, including conceptual, logical, and physical data models.\nDefine scalable data lake, data warehouse, and lakehouse architectures on Google Cloud Platform.\nEstablish enterprise data standards, naming conventions, and architecture best practices.\nEvaluate and recommend appropriate data storage and processing patterns for structured and semi-structured data.\nDrive architecture decisions for new business initiatives and digital transformation programmes.\n\nGoogle Cloud Platform (GCP): \nDesign and implement cloud-native data solutions using GCP services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, BigLake, Cloud Composer, Cloud Run, and GKE.\nOptimise data platforms for scalability, performance, reliability, and cost efficiency.\nEnsure secure and compliant cloud architectures by implementing IAM, encryption, and governance best practices.\nCollaborate with cloud engineering teams on Infrastructure as Code (Terraform preferred) and CI/CD automation.\n\nData Engineering and Integration: \nDesign and oversee enterprise ETL/ELT pipelines for batch and real-time data processing.\nBuild scalable integration frameworks across multiple enterprise applications and data sources.\nArchitect streaming data solutions using technologies such as Pub/Sub, Kafka, Spark, or Dataflow.\nEnsure end-to-end data lineage, monitoring, observability, and operational excellence.\nDrive modernisation of legacy data platforms to cloud-native architectures.\n\nAnalytics and Data Enablement: \nDesign semantic and analytical data models for enterprise reporting and business intelligence.\nPartner with analytics teams to develop trusted, reusable, and governed data products.\nEnable self-service analytics by delivering well-documented, high-quality datasets.\nSupport data platforms that can serve advanced analytics and future machine learning initiatives.\n\nData Governance and Security: \nDefine enterprise data governance standards and best practices.\nImplement data quality frameworks, validation rules, and monitoring processes.\nContribute to metadata management, data cataloguing, and lineage initiatives.\nEstablish data contracts, SLAs, and governance policies across business domains.\nEnsure compliance with organisational security and regulatory requirements.\n\nStakeholder Collaboration: \nPartner with Product, Engineering, Business, and Analytics stakeholders to understand data requirements.\nLead architecture reviews, technical discussions, and solution design workshops.\nTranslate complex business requirements into scalable technical solutions.\nMentor data engineers and provide technical guidance across teams.\n\nRequirements: \n10+ years of experience in data architecture, data engineering, or cloud data platform development.\nStrong hands-on experience with Google Cloud Platform (GCP).\nExpertise in BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, BigLake, and Cloud Composer.\nStrong understanding of data lake, data warehouse, and lakehouse architectures.\nExperience with data modelling methodologies, including Relational, Dimensional (Kimball), and Data Vault.\nHands-on experience building large-scale ETL/ELT pipelines.\nStrong SQL expertise and programming experience in Python.\nExperience with distributed data processing frameworks such as Apache Spark/PySpark.\nGood understanding of streaming architectures and event-driven data processing.\nExperience with Infrastructure as Code (Terraform preferred).\nStrong understanding of data governance, security, and metadata management.\nExcellent communication and stakeholder management skills.\nWe are looking for a technology leader who is passionate about building modern, scalable data platforms on Google Cloud Platform.\nYou should have the ability to balance strategic architecture with hands-on technical expertise, collaborate effectively with cross-functional teams, and drive best practices in cloud data engineering and governance.\nThe ideal candidate thrives in a fast-paced environment, enjoys solving complex data challenges, and has a strong foundation in designing enterprise data ecosystems that support business intelligence, analytics, and future innovation.\n\nPreferred: \nExperience working in agile product organisations.\nExposure to Vertex AI or cloud-based machine learning services.\nFamiliarity with modern data catalogue and governance tools such as Collibra, DataHub, and Alation.\nExperience with BI tools such as Looker, Tableau, or Power BI.\nKnowledge of Data Mesh principles and domain-driven data architecture.\nExposure to modern AI/ML-enabled data platforms is an added advantage.\nSkills\nbigquery, elt, etl, gcp, google cloud, google cloud platform","description_format":"text","description_chars":5462,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Mobile Networks","IT Consulting & Digital Transformation"],"lifecycle":[{"event":"open","at":"2026-10-22T19:35:00Z"}],"visa":[],"liveness":{"score":68,"band":"ok","label":"Likely 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