Senior Data Architect

We’re Hiring: Senior Data Architect (Remote)

📌 Location: Remote

📌 Employment Type: Annual Renewable Contract We are seeking a highly experienced Data Architect with deep expertise in the Databricks Lakehouse Platform to design, build, and govern our enterprise data architecture. This is a fully remote role for someone who thrives on independence, ownership, and delivering production-ready solutions at scale.

🔑 Key Responsibilities

Architect and deliver enterprise-grade data solutions from concept to go-live — no templates, no hand-holding.

Own architecture decisions end-to-end: design, documentation, and rollout.

Implement Databricks medallion architecture (Bronze/Silver/Gold) with Delta Lake, Unity Catalog, and Delta Live Tables.

Optimize clusters, workflows, and compute costs with smart orchestration and policies.

Define data platform strategy, standards, and best practices across ingestion, storage, transformation, and consumption.

Lead governance, security, and compliance initiatives (GDPR, CCPA, encryption, masking).

Partner with BI teams to enable self-service analytics via Power BI, Tableau, and other tools.

Mentor engineers and act as the primary technical authority for stakeholders. 🎯 Required Skills & Experience

10+ years in data architecture/engineering, with 4–5+ years hands-on Databricks in production.

Proven ability to independently design and deliver enterprise-scale, production-ready architectures.

Expert-level Databricks (Delta Lake, Unity Catalog, DLT, Workflows, SQL Warehouses).

Strong programming in PySpark, SQL, Python (Scala a plus).

Cloud experience: Azure, AWS, or GCP.

Data modeling expertise: Dimensional, Data Vault, Medallion.

CI/CD & IaC: Git, Terraform, Databricks Asset Bundles.

Integration with BI tools and enterprise systems (SAP, Salesforce).

Certifications (Databricks, Cloud) preferred. 🌟 Soft Skills

Strong communication and executive presentation skills.

Ability to mentor and lead teams.

Track record of delivering solutions that scale across multiple systems and high data volumes.

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