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Role Overview
We are seeking a senior-level Azure Data Platform Engineer with deep expertise in Azure SQL Managed Instance, Azure Data Factory (ADF), and enterprise database administration. This individual will play a hands-on leadership role in managing, troubleshooting, and driving data platform reliability and performance across a complex client environment.
This is not a passive support role. The ideal candidate is someone who will step in, take ownership of data pipelines and database operations, and proactively identify and resolve issues—often in high-pressure or ambiguous situations with demanding stakeholders.
This role is best suited for a practitioner who can balance deep technical execution with client engagement, operate across vendor ecosystems, and lead critical data loading and platform operations end-to-end.
Engagement Focus
Long-term contract supporting a mission-critical data platform
Emphasis on stability, performance improvement, and operational ownership
Requires a resource who can operate independently and lead through ambiguity
Not advisory—this is a hands-on execution and delivery role
Key Responsibilities
Azure SQL Platform Administration & Optimization
Administer and manage Azure SQL Managed Instance and Azure SQL databases in production environments
Perform database performance tuning, including indexing strategies, query plan analysis, and workload optimization
Diagnose and resolve locking, blocking, and concurrency issues
Implement and manage database security, user access, and role-based permissions
Ensure robust backup, recovery, and high availability practices
Data Factory (ADF) Engineering & Operations
Design, build, and maintain ADF pipelines for batch and incremental data loading
Administer ADF environments, including monitoring, scheduling, and failure handling
Troubleshoot pipeline failures, integration issues, and performance bottlenecks
Analyze execution logs and metrics to identify systemic issues in data processing workflows
Ensure pipelines are resilient, scalable, and operationally supportable
Data Load Process Ownership
Take end-to-end ownership of data loading processes, from ingestion through validation
Lead efforts to stabilize, standardize, and improve existing pipelines
Identify root causes of failures and implement durable, repeatable fixes
Coordinate across teams to ensure data availability and integrity
Establish and enforce monitoring, alerting, and operational discipline
Automation & Scripting
Develop and maintain automation using Python and/or PowerShell
Automate operational workflows such as environment validation, monitoring, and remediation
Reduce manual intervention through repeatable scripting solutions
Azure Infrastructure & DevOps Integration
Work within Azure environments to support infrastructure dependencies impacting data workloads
Utilize Azure DevOps (ADO) for:
Managing database schema changes
Versioning and promoting ADF pipelines
Contribute to CI/CD practices for data platform deployments
Delivery & Stakeholder Engagement
Work directly with client stakeholders, internal teams, and third-party vendors
Operate effectively in environments with unclear ownership, legacy systems, or process gaps
Communicate clearly around issues, risks, and remediation strategies
Demonstrate a willingness to take initiative, assume ownership, and drive outcomes
Required Qualifications
7+ years of experience in database administration, data engineering, or data platform operations
Deep hands-on expertise with:
Azure SQL Managed Instance / Azure SQL Database
Azure Data Factory (pipeline development and administration)
Strong experience in SQL query optimization and performance tuning
Proven ability to diagnose and resolve:
Locking/blocking issues
Data pipeline failures
Performance bottlenecks
Experience managing database user access and security administration
Hands-on experience with Python and/or PowerShell scripting
Experience with Azure DevOps (ADO) for managing code and deployments
Strong analytical skills with the ability to interpret logs and debug data processes
Ability to work independently in complex, high-pressure environments
Preferred Qualifications
Experience supporting large-scale or high-volume data environments
Exposure to multi-vendor or hybrid data ecosystems
Familiarity with broader Azure services supporting enterprise data platforms
Prior experience in client-facing or consulting roles
Experience stabilizing or inheriting underperforming data environments
What Success Looks Like
Data pipelines run reliably with minimal disruption
Database performance issues are identified early and resolved quickly
Data load processes are owned, documented, and continuously improving
Stakeholders gain confidence in the platform and its stability
The environment shifts from reactive issue management to proactive control
The individual becomes the go-to resource for platform reliability and execution
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