Senior Data & AI Engineering Consultant

Inter.link

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

Posted 10/27/2026full-timeRemote • Ohio • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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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 transforming raw data into analytics-ready datasets for BI and advanced analytics use cases.

Highest-signal resume keywords

Azure Data Warehouse DesignSQL Transformation SkillsSpark/PySpark Data EngineeringData Quality PracticesClient-Facing Delivery Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLSparkPySparkKQLData Pipeline DevelopmentData ModelingData TransformationData Quality ValidationOrchestrationAutomated Testing

Soft Skills

Strong Communication SkillsStakeholder ManagementClient Alignment

Tools & Technologies

Microsoft FabricAzure Data FactoryPower BIDatabricksADLS Gen2Azure SynapseOneLakeLakehouseData Factory in FabricReal-Time Analytics

Certifications & Qualifications

DP-700PL-300AZ-305

Industry Keywords

Data LakeLakehouseData WarehouseAnalytics-Ready DatasetsSecurity and GovernanceCompliance ControlsBI EnablementAI-Enablement PatternsInfrastructure as CodeCI/CD

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 implementation of ingestion, transformation, and orchestration pipelines using Microsoft Fabric and Azure services
Integrate operational systems, APIs, and third-party data sources
Transform raw data into curated, analytics-ready datasets
Build and maintain analytics-ready data models and schemas
Implement enrichment, business rules, and reusable data 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
Design and implement security, governance, and compliance controls across Azure and Fabric
Facilitate workshops and communicate architecture tradeoffs with client stakeholders and delivery teams
Produce design documents, diagrams, implementation guides, and enablement materials
Support adoption and smooth handoff of delivered solutions

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
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
Preferred: Direct experience with Microsoft Fabric components, including OneLake, Lakehouse, Warehouse, Data Factory in Fabric, and Real-Time Analytics/KQL databases
Preferred: Experience with Azure Data Factory, Synapse, Databricks, ADLS Gen2, and Key Vault
Preferred: Working knowledge of Azure architecture fundamentals across identity, networking, storage, monitoring, resiliency, and cost management
Preferred: Familiarity with AI-enablement patterns such as Azure AI Search, Microsoft Foundry, retrieval-augmented generation, or agent-based solutions
Preferred: Experience implementing CI/CD and Infrastructure as Code
Preferred: Familiarity with semantic modeling and BI enablement patterns
Current Microsoft certifications are valued, especially DP-700, PL-300, and AZ-305
Power Apps experience is a plus
Must be able to work in a client-facing consulting environment

Benefits

Comp & perks

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