Senior Azure Cloud Platform Engineer
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Before you apply
LocationRemote
Work moderemote · United States
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentData & AI Services
Company size201–500 people
PostedSep 25, 2026 · 1mo ago
Verified live17h ago
At a glanceSummarised by Seekless from the posting.
At least 5 years of relevant professional experience in data science, data engineering, or software engineering
At least 3 years building, deploying, and supporting workloads in Microsoft Azure
Bachelor's degree in operations research, business, computer science, data science, information systems, statistics, mathematics, engineering, or a related field, or equivalent demonstrated professional experience
Strong hands-on capability in Microsoft Azure: data storage and compute, identity and access, secure connectivity, deployment automation, monitoring, troubleshooting, and cost management
Working proficiency building Power BI reports and semantic models, using Power Query and DAX
Practical experience with Microsoft Fabric: workspaces, OneLake, lakehouses or warehouses, and data pipelines or notebooks
Working proficiency with Azure Databricks: notebooks, PySpark or Spark SQL, Delta Lake tables, and scheduled jobs
Strong proficiency in Python and SQL for data preparation, analysis, reusable components, and backend processing
Understanding of analytical data models, schemas, data grain, join cardinality, missing values, time alignment, and traceability across data sources and reports
Apply version control, code review, automated testing, and controlled releases
Understand APIs, persistent state, long-running processing, and safe recovery from failures
Demonstrate agentic development capability with tools such as Claude Code and OpenAI Codex
Translate ambiguous business questions into measurable analytical problems
Apply statistical and mathematical reasoning, including weighted metrics, uncertainty, validation design, data leakage, and the distinction between association and causation
Assess data completeness, consistency, and suitability before choosing analytical methods
Evaluate models and analytical results against meaningful baselines
Reproduce unexpected behavior, construct small diagnostic examples, and use evidence to distinguish data, modeling, and implementation problems
Design reproducible experiments and regression and integration tests
Diagnose performance and usability issues involving large datasets, long-running tasks, stale results, and failure reporting
Explain methods, tradeoffs, uncertainty, and limitations clearly to technical and nontechnical stakeholders
Take ownership of quality, follow issues through to a verified resolution, and communicate progress and blockers clearly
Distinguish what the evidence establishes from what remains an assumption, and document decisions so others can reproduce the work
Balance analytical rigor with practical delivery, seek feedback early, and recognize when deeper domain or platform expertise is needed
Master's degree is a plus but is not required
Manufacturing experience and/or experience in the Microsoft partner channel
Manufacturing knowledge, such as production planning, bills of material, material requirements planning, scheduling, procurement, or inventory processes
Microsoft partner-channel experience in technical consulting, solution architecture, implementation, or integrations, including exposure to Dynamics 365 or other ERP systems
Predictive modeling, time-series forecasting, simulation, mathematical optimization, or model deployment and monitoring
Infrastructure as code with Bicep or Terraform, CI/CD with Azure DevOps or GitHub Actions, and automated environment provisioning
FastAPI, React, JavaScript, data visualization, and interactive analytical applications
Relevant Microsoft or Databricks certifications
Skills
Python
SQL
Microsoft Azure
Power BI
Microsoft Fabric
Azure Databricks
PySpark
Spark SQL
Delta Lake
Claude Code
OpenAI Codex
ADLS Gen2
Azure SQL
Entra ID
Key Vault
Azure Monitor
Power Query
DAX
Bicep
Terraform
Azure DevOps
GitHub Actions
FastAPI
React
JavaScript
Dynamics 365
Benefits
Unlimited PTO
401(k)
Stipend for home office expenses
Health insurance
Dental insurance
Vision insurance
Health savings account
Flexible spending account
Life insurance
Disability insurance
Training support
Certification support
Continuing education support
About the company
Through passion and deep industry expertise, MCA Connect helps manufacturers succeed by unlocking innovation with actionable business insights. Our strategic solutions, innovation, and industry intelligence help manufacturers gain visibility, improve profitability, and achieve a competitive edge.
Established in 2002, MCA Connect has grown into one of the largest US-based solution partners in Microsoft Business Applications and Azure Data & AI / Digital & App Innovation. Our Microsoft Specialties include Finance and Supply Chain, Analytics on Azure, Data Warehouse Migration, and Power Platform. We’re also a fifteen-time Microsoft Partner of the Year and three-time Inc. Best Workplaces award winner.
About the role
Senior Azure Cloud Platform/Data Science Engineer
Planning and Decision Systems
Location
Remote with light travel as needed to client sites
Employment Type
Full-time
We are seeking a Senior Data Science Engineer with strong Python and SQL skills, quantitative judgment, and demonstrated strength in Azure. The role combines data science, data engineering, and software development. Practical working proficiency in Power BI, Microsoft Fabric, and Azure Databricks is required, alongside effective use of AI development tools and independent validation of results.
Experience and education
At least 5 years of relevant professional experience in data science, data engineering, or software engineering, including at least 3 years building, deploying, and supporting workloads in Microsoft Azure. Candidates should demonstrate ownership of deployed solutions and the ability to troubleshoot operational issues.
A bachelor’s degree in operations research, business, computer science, data science, information systems, statistics, mathematics, engineering, or a related field, or equivalent demonstrated professional experience. A master’s degree is a plus but is not required. A PhD is not required.
Required platform and technical skills
•
Microsoft Azure: Strong hands-on capability in data storage and compute, identity and access, secure connectivity, deployment automation, monitoring, troubleshooting, and cost management. Relevant services include ADLS Gen2, Azure SQL, Entra ID, managed identities, Key Vault, and Azure Monitor.
•
Power BI: Working proficiency building reports and semantic models, using Power Query and DAX, defining relationships and measures, configuring refresh and row-level security, and reconciling reported metrics to source data.
•
Microsoft Fabric: Practical experience with workspaces, OneLake, lakehouses or warehouses, and data pipelines or notebooks. Ability to follow data lineage, manage appropriate access, and diagnose processing or reporting issues.
•
Azure Databricks: Working proficiency with notebooks, PySpark or Spark SQL, Delta Lake tables, and scheduled jobs. Ability to investigate failed runs and understand compute configuration, data permissions, and performance tradeoffs.
•
Python and SQL: Strong proficiency in data preparation, analysis, reusable components, and backend processing. Ability to read unfamiliar code, explain its behavior, and improve its maintainability.
•
Data modeling and integration: Understand analytical data models, schemas, data grain, join cardinality, missing values, time alignment, and traceability across data sources and reports.
•
Software delivery: Apply version control, code review, automated testing, and controlled releases. Understand APIs, persistent state, long-running processing, and safe recovery from failures.
AI assisted development
Demonstrate agentic development capability with tools such as Claude Code and OpenAI Codex. Break work into bounded tasks, provide repository context and constraints, direct coding agents, and iterate through implementation, testing, and debugging. Review generated changes, manage branches and tool permissions, protect sensitive information, and independently verify code and analytical results before release.
Analytical and problem solving skills
•
Translate ambiguous business questions into measurable analytical problems, with explicit assumptions, objectives, constraints, and success criteria.
•
Apply statistical and mathematical reasoning, including weighted metrics, uncertainty, validation design, data leakage, and the distinction between association and causation.
•
Assess data completeness, consistency, and suitability before choosing analytical methods. Reconcile inputs, intermediate calculations, and reported outputs.
•
Evaluate models and analytical results against meaningful baselines. Distinguish improved model performance from changes in data selection, aggregation, or assumptions.
•
Reproduce unexpected behavior, construct small diagnostic examples, and use evidence to distinguish data, modeling, and implementation problems.
•
Design reproducible experiments and regression and integration tests. Verify behavior across processing, storage, APIs, and reporting boundaries.
•
Diagnose performance and usability issues involving large datasets, long-running tasks, stale results, and failure reporting.
•
Explain methods, tradeoffs, uncertainty, and limitations clearly to technical and nontechnical stakeholders.
Preferred experience
Manufacturing experience and/or experience in the Microsoft partner channel is especially valuable. The following qualifications strengthen a candidate profile; depth in every area is not expected.
•
Manufacturing knowledge, such as production planning, bills of material, material requirements planning, scheduling, procurement, or inventory processes.
•
Microsoft partner-channel experience in technical consulting, solution architecture, implementation, or integrations, including exposure to Dynamics 365 or other ERP systems.
•
Predictive modeling, time-series forecasting, simulation, mathematical optimization, or model deployment and monitoring.
•
Infrastructure as code with Bicep or Terraform, CI/CD with Azure DevOps or GitHub Actions, and automated environment provisioning.
•
FastAPI, React, JavaScript, data visualization, and interactive analytical applications.
•
Relevant Microsoft or Databricks certifications. Certifications support, but do not replace, demonstrated practical capability.
Domain learning and collaboration
Learn unfamiliar business concepts through collaboration with subject-matter experts. Restate proposed methods accurately, identify their assumptions, test their implementation, and question implausible results. Advanced operations research expertise is welcome; strong quantitative foundations and demonstrated learning ability are essential.
Professional expectations
•
Take ownership of quality, follow issues through to a verified resolution, and communicate progress and blockers clearly.
•
Distinguish what the evidence establishes from what remains an assumption, and document decisions so others can reproduce the work.
•
Balance analytical rigor with practical delivery, seek feedback early, and recognize when deeper domain or platform expertise is needed.
Why work for MCA Connect?
Our compensation plan offers one of the best bonus structures in the industry. Along with this we also offer a generous benefit package:
· Work/Life Balance with Unlimited Paid Time Off (UPTO)
· 401k Plan with Company Matching Contribution
· Monthly Stipend for Home Office Expenses
· Subsidized Medical, Dental and Vision Coverage
· Health Savings and Flexible Spending Accounts
· Company Paid Life and Disability Insurance
· Training, Certification and Continuing Education Support
MCA Connect offers limitless opportunities for personal and professional growth in a stimulating, challenging, and performance-oriented work culture where you can share your ideas and make impactful daily contributions. Our employees are highly motivated and talented individuals dedicated to developing, marketing, and selling products designed to deliver value for mid-market and enterprise-size manufacturing, distribution, and energy companies. We take the time to train our consultants so that they understand the industries we serve and can deliver best practices, proven methodologies, and ongoing industry expertise to our clients.
Legal
MCA Connect is an Equal Opportunity Employer. MCA Connect promotes equal employment opportunity to all employees and applicants and does not discriminate on the basis of race, religion, color, creed, national origin, sex, age, sexual/gender orientation, status as a protected disabled or Vietnam Era Veteran, disability, or any other legally protected status. We firmly believe our differences make us stronger!