Senior Data & AI Engineering Consultant

Inter.link

. Lead client discovery to understand business goals, data landscape, constraints, and success metrics .

Posted 11/3/2026full-timeMason • Ohio • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and delivering modern analytics platforms using Azure and Microsoft Fabric, with a strong focus on data quality, security, and governance. Proficient in building reliable data pipelines and analytics-ready data models to support business intelligence and advanced analytics use cases.

Highest-signal resume keywords

Azure Data ArchitectureSQL Transformation SkillsSpark/PySpark Data EngineeringData Quality PracticesMicrosoft Fabric Components

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

SQLSparkPySparkKQLData Pipeline DevelopmentData ModelingData Quality ValidationOrchestrationAutomated TestingCI/CD Implementation

Soft Skills

Strong Communication SkillsStakeholder Management

Tools & Technologies

Microsoft FabricAzure Data FactoryPower BIDatabricksADLS Gen2Key VaultAzure Synapse

Certifications & Qualifications

DP-700PL-300AZ-305

Industry Keywords

Data LakeLakehouseData WarehouseAnalytics PlatformsGovernance ControlsComplianceAI Enablement Patterns

Tech Stack

Tools & technologies

AzurePySparkSparkSQLVault

About the role

Key responsibilities & impact

Lead client discovery to understand business goals, data landscape, constraints, and success metrics
Translate discovery findings into clear delivery plans
Design and recommend data lake, lakehouse, data warehouse, and analytical data store architectures on Azure and Microsoft Fabric
Implement or guide ingestion, transformation, and orchestration pipelines using Microsoft Fabric and Azure services
Integrate operational, API, and third-party data sources into curated datasets
Build and maintain analytics-ready data models and schemas
Implement enrichment, business rules, and reusable patterns
Enable SQL, Spark/PySpark, Spark SQL, and KQL compute engines against shared datasets
Prepare governed data products and reusable datasets for BI, advanced analytics, and AI use cases
Establish data quality practices including validation, reconciliation, testing, and monitoring
Troubleshoot failures and improve pipeline resiliency
Optimize transformations, query performance, and pipeline execution for service-level and cost objectives
Implement logging, metrics, and operational runbooks
Support deployments, cutovers, and hypercare as needed
Design and implement security, governance, and compliance controls across Azure and Fabric
Facilitate workshops and communicate architecture tradeoffs with client stakeholders and technical teams
Produce design documents, diagrams, implementation guides, and enablement materials

Requirements

What you’ll need

Experience designing and delivering modern analytics platforms using lakehouse and/or data warehouse patterns on Azure and/or Microsoft Fabric, including client-facing delivery
Strong SQL skills with experience building transformations and dimensional or analytical models
Hands-on experience with Spark (PySpark/Spark SQL) and/or KQL for data engineering and analytics workloads
Experience applying software engineering practices to data solutions, including modular design, source control, automated testing, code review, and technical documentation
Experience building reliable data pipelines, including orchestration, scheduling, error handling, and automated monitoring
Knowledge of data quality practices, including validation, reconciliation, testing, incident triage, and root-cause analysis
Working knowledge of Power BI, including semantic modeling concepts; Power Apps experience is a plus
Understanding of security and governance concepts for data platforms, including access controls, least privilege, compliance, and lineage
Strong communication skills, with the ability to present recommendations, align stakeholders, and manage expectations in a client environment
Direct experience with Microsoft Fabric components, including OneLake, Lakehouse, Warehouse, Data Factory in Fabric, and Real-Time Analytics/KQL databases, is preferred
Experience with Azure Data Factory, Synapse, Databricks, ADLS Gen2, and Key Vault is preferred
Working knowledge of Azure architecture fundamentals across identity, networking, storage, monitoring, resiliency, and cost management is preferred
Familiarity with AI-enablement patterns such as Azure AI Search, Microsoft Foundry, retrieval-augmented generation, or agent-based solutions is valued
Experience implementing CI/CD and Infrastructure as Code is preferred
Familiarity with semantic modeling and BI enablement patterns is preferred
Current relevant Microsoft certifications are valued, especially DP-700, PL-300, and AZ-305
Equivalent current Microsoft credentials and experience mentoring or enabling client teams are welcome

Benefits

Comp & perks

Stability and benefits usually found at enterprise firms
Family-first attitude
Innovative, fun, and collaborative environment
Best Places to Work Award recognition
Equal-opportunity employment