Databricks SME
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 11h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 270d ago
The date the source published, not the day we noticed it (2026-01-07). Last seen at its source 3h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Georgia, United States
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
bamboohr employer's own board first seen 11h ago · last seen 3h ago
The listing
Key Responsibilities:
Architecture & Platform Design
- Design enterprise Databricks Lakehouse architectures aligned with the Databricks Well-Architected Framework
- Define reference architectures for batch, streaming, analytics, and ML workloads
- Select and standardize cluster, compute, and workspace architectures
- Design multi-workspace strategies (dev/test/prod, shared vs. isolated)
- Ensure architectures meet scalability, availability, and performance requirements
Well-Architected Framework Alignment
Apply Databricks best practices across all pillars, including:
- Security & Governance (Unity Catalog, IAM, data access controls)
- Reliability & Resilience (job retries, checkpointing, failure isolation)
- Performance Efficiency (cluster sizing, autoscaling, caching)
- Cost Optimization (compute policies, workload separation, monitoring)
- Operational Excellence (monitoring, automation, CI/CD, runbooks)
Implementation & Engineering
- Lead Databricks workspace, cluster, and Unity Catalog implementations
- Implement Delta Lake, Delta Live Tables (DLT), and Structured Streaming
- Build and optimize ETL/ELT pipelines using Spark and SQL
- Integrate Databricks with cloud services (S3/ADLS/GCS, IAM, Key Vault, networking)
- Establish CI/CD pipelines for notebooks, jobs, and infrastructure
Security, Governance & Compliance
- Implement Unity Catalog for centralized governance
- Define data classification, lineage, and audit strategies
- Enforce least-privilege access and secure networking patterns
- Support compliance requirements (HIPAA, SOC 2, PCI, GDPR as applicable)
Operations & Optimization
- Monitor platform health, performance, and cost
- Troubleshoot production issues across jobs, clusters, and data pipelines
- Perform workload tuning and cost-performance optimization
- Define SLOs, alerts, and operational metrics
Collaboration & Leadership
- Partner with Data Engineering, Analytics, ML, Platform, and Security teams
- Translate business requirements into technical architectures
- Provide architectural guidance and technical mentorship
- Communicate risks, tradeoffs, and recommendations to leadership
Required Qualifications:
Experience
- 7+ years in data engineering, analytics, or platform architecture
- 3–5+ years hands-on Databricks experience in production environments
- Proven experience applying the Databricks Well-Architected Framework
- Experience designing cloud-native lakehouse architectures
- Experience supporting mission-critical data platforms
Technical Skills
- Databricks Lakehouse Platform
- Apache Spark (PySpark / Scala / Spark SQL)
- Delta Lake, Delta Live Tables, Structured Streaming
- Unity Catalog (governance, lineage, access controls)
- Cloud platforms: AWS, Azure, or GCP
- Infrastructure as Code (Terraform strongly preferred)
- CI/CD tools (GitHub Actions, Azure DevOps, GitLab, etc.)
- Data formats and protocols (Parquet, JSON, Avro)
Certifications Required:
- Databricks Certified Data Engineer Professional
- Databricks Certified Professional Architect (or equivalent advanced certification)
Preferred / Additional Certifications
- AWS Certified Solutions Architect (Associate or Professional)
- Azure Solutions Architect Expert
- Google Professional Data Engineer
- Databricks Machine Learning Professional
- Snowflake or other cloud data platform certifications
Soft Skills
- Strong architectural decision-making and documentation skills
- Excellent communication with technical and non-technical stakeholders
- Ability to lead design reviews and architecture governance forums
- Strong troubleshooting and performance-tuning mindset
Nice-to-Have Experience
- MLflow and MLOps architectures
- Real-time analytics and streaming pipelines
- Multi-region or cross-account data architectures
- Consulting or MSP delivery experience