{"id":2786630,"url":"https://alion.io/job/syrencloud-data-architect","title":"Data Architect","company":{"id":4442673,"name":"Syren","domain":"syrencloud.com","url":"https://alion.io/company/syrencloud","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"GCP","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"CI/CD","optional":true},{"name":"Data Vault","optional":true},{"name":"Dimensional Modeling","optional":true}],"status":"live","first_seen_at":"2026-04-07T09:14:35Z","employer_posted_date":"2026-04-07","last_verified_at":"2026-10-17T18:55:14Z","board_verified":true,"closed_at":null,"days_open":193,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":193},"description":"Role Overview\nWe are looking for an experienced Data Architect with strong expertise in Databricks and cloud-based data platforms across Azure, AWS, or Google Cloud Platform (GCP). The ideal candidate will be responsible for designing scalable, secure, high-performance data architectures and modern lakehouse solutions that support enterprise data engineering and analytics requirements.\nThe candidate should have a strong understanding of data modelling, data integration, cloud architecture, data governance, and performance optimization, along with the ability to translate business requirements into robust technical solutions.\nKey Responsibilities\nDesign and implement scalable, secure, and cost-effective data architectures using Databricks on Azure, AWS, or GCP.\nDefine end-to-end lakehouse architecture, including data ingestion, transformation, storage, processing, and consumption layers.\nDevelop architecture standards and best practices for data engineering, data modelling, data integration, and platform design.\nLeverage Databricks capabilities, including Delta Lake, Unity Catalog, and the Medallion Architecture, wherever appropriate.\nDesign and optimize batch and streaming data pipelines using Apache Spark, PySpark, SQL, and related technologies.\nEstablish data governance, security, access control, data quality, metadata management, and lineage practices.\nCollaborate with data engineers, analytics teams, business stakeholders, and cloud/platform teams to deliver reliable data solutions.\nIdentify and resolve architectural challenges related to scalability, performance, reliability, and cloud cost optimization.\nEvaluate existing data platforms and recommend modernization, migration, and optimization strategies.\nDocument architecture designs, technical standards, data flows, and implementation guidelines.\nRequired Skills and Qualifications\nStrong experience in data architecture, data platform design, or enterprise data engineering.\nHands-on experience with Databricks and cloud-based data platforms.\nStrong expertise in at least one cloud platform: Microsoft Azure, AWS, or GCP.\nSolid understanding of lakehouse architecture, Delta Lake, and the Medallion Architecture.\nProficiency in SQL and practical knowledge of Python, PySpark, and Apache Spark.\nExperience designing data models, data pipelines, and data integration solutions.\nUnderstanding of data governance, security, access management, data quality, and metadata management.\nExperience with performance tuning, scalability, reliability, and cost optimization of data platforms.\nAbility to translate business and technical requirements into scalable architectural solutions.\nStrong communication, problem-solving, stakeholder management, and technical documentation skills.\nPreferred Qualifications\nExperience with Databricks Unity Catalog, Delta Live Tables / Lakeflow Declarative Pipelines, and workflow orchestration.\nKnowledge of dimensional modelling, Data Vault, enterprise data modelling, or similar approaches.\nExperience with cloud-native storage, data services, and orchestration tools.\nExposure to CI/CD, infrastructure automation, monitoring, and 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