JR-214082 Data Architect

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.

About this job:
We 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.

Location: LATAM (remote)

How you'll make an impact:
· 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;
· Environment promotion — dev QA prod promotion lane, including deployment-pipeline enabler work;
· UAT enablement — active fix-it engineer supporting Genie/dashboard UAT test cycles;
· Cross-domain platform contribution — commit directly to the shared, reusable Databricks platform template (consumed by multiple domains);
· 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;
· 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;
· 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;
· 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);
· 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.

What makes you a great fit:
· Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field;
· 10+ years of experience in data engineering and data architecture roles;
· 4+ years of hands-on experience with Databricks;
· Experience with the insurance industry (Nice to have);
· Strong knowledge of AWS cloud platforms;
· Exposure to Large Language Models (LLMs), Generative AI concepts, prompt engineering, and AI-assisted development tools.

Core platform skills:
· Delta Lake medallion architecture (bronze silver gold platinum) and Unity Catalog schema/metric-view design;
· Databricks Asset Bundles for CI/CD-style promotion across dev/QA/prod environments;
· Databricks Jobs orchestration and freshness/volume monitoring design — building alerting tables and configuration from scratch, not just consuming existing ones;
· Data quality framework design — DataPact contracts and DQX checks;
· AI/BI enablement — Genie space configuration/semantics (including multi-environment automation) and Lakeview dashboard build and defect resolution;
· 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;
· 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;
· 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;
· 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;
· 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.

• Excellent written and verbal communication skills in English;
  · Ability to work in a global, multi-national company;
  · Ability to lead conversations with both technical and business representatives;
  · Proven ability to work both independently and as a part of an international project team.

If 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. Are you ready to spark the tech with us?

Originally posted on Himalayas