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Technical Engineer
Job in
Hartford, Hartford County, Connecticut, 06112, USA
Listed on 2026-06-02
Listing for:
Collabera Technologies
Full Time
position Listed on 2026-06-02
Job specializations:
-
IT/Tech
Data Engineering, Cloud Computing
Job Description & How to Apply Below
Contract:
Hartford, Connecticut, US
Salary Range: 40.00 - 55.00 | Per Hour
Job Code: 369623
End Date:
Days Left: 27 days, 3 hours left
Apply
Title: Databricks Architect/Admin
Location: Hartford, CT 06183
Duration: 6 months (Possible Extension)
Pay Range: $40/hr - $55/hr
The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, (paid time , paid sick and safe time , hours of paid vacation time, weeks of paid parental leave, paid holidays annually - AS Applicable)
Position Summary
- The Databricks Architect/ADMIN is a senior individual contributor responsible for the design, implementation, and continuous optimization of the enterprise Databricks platform.
- This role serves as the technical authority for all aspects of the Databricks environment - including workspace governance, Unity Catalog, cluster and compute strategy, data pipeline architecture, and cost management.
- The Architect works in close partnership with data engineering, analytics, and infrastructure teams, and operates within a broader multi-platform data ecosystem that includes Ab Initio and Fivetran.
- A strong background in Unix/Linux systems administration and scripting is essential, as the role requires deep engagement with the underlying compute infrastructure supporting the platform.
Platform Architecture & Design
• Architect and govern the enterprise Databricks environment, including workspace topology, Unity Catalog structure, and access control frameworks.
• Define and enforce standards for cluster configuration, runtime versions, instance pool utilization, and auto-scaling policies.
• Design scalable, performant data pipeline patterns using Delta Live Tables, Databricks Workflows, and structured streaming.
• Establish architectural standards for Delta Lake - including table formats, partitioning strategies, Z-ordering, and OPTIMIZE/VACUUM scheduling.
• Lead platform integration design with upstream ingestion tools including Fivetran and Ab Initio, ensuring reliable, governed data delivery.
Unix/Linux Infrastructure & Operations
• Administer and troubleshoot Unix/Linux environments underpinning Databricks compute nodes, init scripts, and cluster lifecycle management.
• Develop and maintain shell scripts (Bash) and Python automation for platform operations, monitoring, log aggregation, and maintenance tasks.
• Manage file system operations, permission structures, and data movement tasks in Linux-based storage and compute environments.
• Support EC2/VM-level diagnostics and tuning in coordination with infrastructure and cloud engineering teams.
Cost Management & Optimization
• Own DBU consumption tracking and reporting; proactively identify optimization opportunities across jobs, interactive clusters, and SQL warehouses.
• Implement and maintain cost attribution models to support chargeback or showback reporting by team, product, or LOB.
• Partner with the Senior Director on capacity planning, contract utilization forecasting, and multi-year commitment management.
Governance, Security & Compliance
• Design and implement data governance frameworks within Unity Catalog, including lineage, tagging, and access auditing.
• Collaborate with Cybersecurity to ensure platform configurations satisfy enterprise security controls, including secrets management, network isolation, and encryption.
• Support audit and compliance activities by maintaining documentation of platform configurations, access policies, and data classification standards.
Automation & Artificial Intelligence
• Design and implement end-to-end automation frameworks for platform operations, including cluster lifecycle management, job scheduling, alerting, and self-healing workflows.
• Leverage Databricks AutoML, MLflow, and Model Serving capabilities to support the operationalization of machine learning models within the enterprise data platform.
• Integrate AI-assisted development…
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