Databricks Architect
Applexus Technologies, LLC
United States
28 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source
Tech stack
Amazon Web Services
Microsoft Azure
Big Data
Continuous Integration
Information Engineering
Identity and Access Management
Python (Programming Language)
Performance Tuning
SQL Databases
Cloud Platform System
Data Lakes
Pyspark
+5 more
Deployment Automation
Data Management
Software Version Control
Data Pipelines
Databricks
Job description
You will partner closely with the Databricks field team shaping joint solutions, supporting co-sell pursuits, and occasionally participating in roadshows and partner events. The primary focus is delivery excellence; the GTM dimension adds strategic reach., * Architecture & Delivery: Design Databricks Lakehouse platforms using Delta Lake; define reference patterns for ingestion, transformation, and consumption layers.
- Data Engineering: Build and maintain batch and streaming pipelines with Python, PySpark, and SQL; implement data quality and validation frameworks.
- Governance & Security: Implement Unity Catalog in production - governance, lineage, auditing, access controls, and secure sharing.
- Performance & Cost: Optimize workloads end-to-end; establish cluster policies, tagging, and cost controls.
- Platform Standards: Drive CI/CD, environment promotion (dev/test/prod), and engineering best practices across teams.
- Operational Excellence: Define monitoring, alerting, incident response, and SLA/SLO processes; implement observability across pipelines.
- Technical Leadership: Mentor engineers, lead design and code reviews, and shape the practice roadmap.
- Partner Engagement: Collaborate with the Databricks partnership team on joint offerings, co-sell activity, and select roadshow and field events.
Requirements
- 10+ years in data engineering or architecture, including 3+ years in technical leadership capacity.
- Databricks mastery: Delta Lake, Unity Catalog, Workflows/Jobs, performance tuning - in production environments.
- Advanced Python, PySpark & SQL with large-scale data processing and optimization experience.
- Cloud platform fluency on at least one major hyperscaler (AWS, Azure, or GCP) - IAM, networking, observability, cost management.
- CI/CD expertise for data platforms - testing, packaging, version control, and deployment automation.
- Stakeholder management skills with the ability to translate architecture into business outcomes for both technical and executive audiences.
- Databricks ecosystem awareness - familiarity with partner programs, joint GTM, and co-sell dynamics is a plus, not a prerequisite., An architect with a consulting or services background who has delivered Databricks platform programs end-to-end. You are hands-on, entrepreneurial, and ready to own delivery outcomes while building practice capability alongside you.
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