{"id":2583132,"url":"https://alion.io/job/customertimes-jr-214082-data-architect","title":"JR-214082 Data Architect","company":{"id":3808977,"name":"Customertimes","domain":"customertimes.com","url":"https://alion.io/company/customertimes","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AR","BR","MX","AG","AW","BS","BB","BZ","BM","BO","VG","BQ","KY","CL","CR","CW","DM","DO","EC","SV","FK","GF","GD","GP","GT","GY","HT","HN","JM","MQ","MS","NI","PA","PY","PE","PR","KN","LC","PM","SX"],"hiring_countries_total":45,"salary":null,"salary_estimate":{"min_usd":58000,"max_usd":148000,"period":"year","method":"global_role_seniority_cell","sample_n":578},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Claude","optional":false},{"name":"Databricks","optional":false},{"name":"Least Privilege","optional":false},{"name":"AWS","optional":true},{"name":"CI/CD","optional":true},{"name":"Delta Lake","optional":true},{"name":"GitHub Actions","optional":true},{"name":"LLM","optional":true},{"name":"MLFlow","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-14T23:40:36Z","employer_posted_date":null,"last_verified_at":"2026-10-14T23:40:36Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Hello, our name is Customertimes, but you can call us CT. We are a global digital engineering, product development, and technology consulting company. Headquartered in New York, we have a team of 1000+ experts working across 65+ countries.\nAbout this job:\nWe are seeking an architecture-level engineer to serve as a primary designer and developer on our Databricks Platform Modernization initiative. This role spans medallion architecture, greenfield build-out, data quality processes, cross-team UAT enablement, and AI/ML use case delivery.\nLocation: LATAM (remote)\nHow you'll make an impact:\n· Greenfield architecture — medallion architecture (silver/gold), entity relationship model, and data contracts; includes but is not limited to standardization, cleansing, deduplication, and merge logic; ensuring that Databricks best practices and internal Enterprise Architecture processes are followed;\n· Environment promotion — dev QA prod promotion lane, including deployment-pipeline enabler work;\n· UAT enablement — active fix-it engineer supporting Genie/dashboard UAT test cycles;\n· Cross-domain platform contribution — commit directly to the shared, reusable Databricks platform template (consumed by multiple domains);\n· Release governance — operate within a formal, peer-reviewed promotion model where production releases require an approved change ticket, reflecting comfort with enterprise change-control process, not just technical delivery;\n· Knowledge transfer — provide ongoing knowledge transfer, assist teams as they upskill and begin to take over work, and ensure appropriate documentation is available for future onboarding;\n· Security-conscious automation design — design least-privilege automation (e.g., scoped bot credentials limited to a single target repository, validated with an explicit smoke test) rather than broad-access shortcuts;\n· AI/ML platform enablement — partner with Enterprise Architecture and ML teams to design feature pipelines, model-serving architecture, and governance of ML artifacts (models, features, vector indexes);\n· GenAI capability evaluation — assess and pilot new GenAI/agentic capabilities (e.g., Claude-based tooling, agent frameworks) for data engineering and semantic-layer workflows before wider adoption.\nWhat makes you a great fit:\n· Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field;\n· 10+ years of experience in data engineering and data architecture roles;\n· 4+ years of hands-on experience with Databricks;\n· Experience with the insurance industry (Nice to have);\n· Strong knowledge of AWS cloud platforms;\n· Exposure to Large Language Models (LLMs), Generative AI concepts, prompt engineering, and AI-assisted development tools.\nCore platform skills:\n· Delta Lake medallion architecture (bronze silver gold platinum) and Unity Catalog schema/metric-view design;\n· Databricks Asset Bundles for CI/CD-style promotion across dev/QA/prod environments;\n· Databricks Jobs orchestration and freshness/volume monitoring design — building alerting tables and configuration from scratch, not just consuming existing ones;\n· Data quality framework design — DataPact contracts and DQX checks;\n· AI/BI enablement — Genie space configuration/semantics (including multi-environment automation) and Lakeview dashboard build and defect resolution;\n· CI/CD and release engineering — GitHub Actions-based promotion pipelines (PR - gated dev - QA - prod), Databricks Asset Bundle validation gates, and OIDC-based cloud authentication in place of long-lived secrets;\n· Data reconciliation engineering — designing formal, machine-checked contracts for data conservation and cross-system parity (e.g., versioned-state recovery, parity-witness scoping) rather than one-off reconciliation scripts;\n· AI/ML platform architecture — designing Unity Catalog-governed feature tables and ML-ready gold/platinum layers, and integrating MLflow experiment tracking and model registry into the platform's existing promotion model;\n· GenAI/LLM enablement on Databricks — architecting vector search and retrieval-augmented generation (RAG) pipelines, model-serving endpoints, and extending the existing Genie AI/BI semantic layer toward broader GenAI use cases;\n· AI-assisted engineering practices — using Claude and other AI coding/review tooling as part of the build and review workflow, consistent with platform best practices.\nOther skills:\n\nExcellent written and verbal communication skills in English;\n· Ability to work in a global, multi-national company;\n· Ability to lead conversations with both technical and business representatives;\n· Proven ability to work both independently and as a part of an international project team.\n\nIf you're looking to contribute to global projects, grow your skills, shape the way you work, and be part of a connected international community — Customertimes is the place to build your next career chapter. 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