Senior DevOps Data Engineer

Summary of Duties & Responsibilities

Our client is seeking a driven, passionate Sr DevOps Data Engineer experienced with developing DevOps/MLOps solutions for Azure Services. This individual has a site reliability engineer mindset, has technical depth and hands-on experience of DevOps practices, and works well with a team. The Sr DevOps Data Engineer provides solutions and support to the entire delivery pipeline to facilitate improved collaboration, version control, standardization of environments, continuous integration, continuous deployment, continuous delivery with an emphasis on using automation to improve quality checks and deployment efficiencies. Expected to have hands on technical experience in infrastructure setup, configuration management, and source code version control.

Essential Functions

• Design and implement solutions to automate the CI/CD pipelines for Big Data applications
• Build and maintain data pipelines for analytics and model training
• Build systems that dynamically scale
• Version Control, branching and merging
• Infrastructure provisioning, configuration, management, and monitoring
• Plan Deployments for high availability
• Develop and document processes that support development and production maintenance
• Identify, troubleshoot, and resolve system and deployment issues
• Collaborate with multiple feature development teams in an Agile environment to identify infrastructure needs and requirements for building, deploying their applications into shared environments
• Work closely with development teams as SME to ensure deployable solutions that support best practices
• Define, enforce, and mentor software configuration management implementation standards and best practices, including driving the depth, coverage and quality technical reviews
• Able to work in a fast-paced, collaborative team environment
• Evaluate and recommend new tools, software, or practices that contribute to overall improvement
• Translate business goals (time-to-market, cost control, risk reduction, scalability) into technical delivery decisions. This means prioritizing work based on business impact, not personal technical preference
• Communicate complex technical risks, tradeoffs, and progress in clear, executive-friendly language is critical. This includes framing DevOps issues as business risks or enablers, using concise narratives, visuals, and metrics rather than deep technical detail unless requested
• Own delivery outcomes, not just enable them. This includes taking responsibility for delivery timelines, failure modes, post-incident learning, and continuous improvement - while aligning expectations clearly with business stakeholders

Skills & Competencies

• Experience designing, implementing and supporting deployments of large-scale data intensive applications and data lakes
• Strong expertise building CI/CD pipelines leveraging Azure DevOps Pipeline
• Hands-on experience and solid understanding of Azure products such as Azure Databricks, Azure Data Lake, Azure Key Vault
• Experience with Azure Data suite (i.e Data Factory, Azure SQL and Azure Synapse), Kubernetes Services and Azure Machine Learning Services
• Experience with Azure DevOps Repos, Pipelines, Boards and Artifacts or comparable tools
• Strong experience in Infrastructure as Code
• Strong knowledge of configuration management tools
• Excellent troubleshooting skills in resolving application deployment and cloud infrastructure issues in a distributed big data architecture
• Hands-on experience in building and deploying big data infrastructure in Azure
• Strong experience building machine learning pipelines
• Strong Coding/Scripting experience in Python, PowerShell
• Experience in an Agile environment and DevOps practices
• Excellent analytical and problem-solving skills with a high aptitude to learn
• Excellent written and verbal communication skills
• Strong interpersonal and presentation skills
• Strong organizational skills, with the ability to effectively prioritize and multi-task

Education or Prior Work Experience

• Bachelors degree or 6 or more years of work-related experience
• 5+ years of deep, practical expertise installing, configuring, and maintaining enterprise-scale software products and solutions
• Azure Certifications or equivalent cloud computing certification