Senior Data & AI Engineering Consultant

Interlink Cloud Advisors, Inc.•Landen, OH

About The Position

Interlink Cloud Advisors is seeking a senior, client-facing consultant to help clients build modern, scalable data platforms on Microsoft Azure and Microsoft Fabric. The role spans discovery, architecture, engineering, governance, and client enablement. The consultant leads discovery, designs pragmatic architectures, and delivers end-to-end solutions that turn raw data into trusted, analytics-ready datasets for BI, reporting, advanced analytics, and AI use cases. Solutions should be secure, governed, maintainable, cost-conscious, and operationally ready. The consultant works across Microsoft Fabric—including OneLake, Lakehouse, and Warehouse—and Azure data services. They collaborate with client stakeholders and technical teams, communicate architecture recommendations and tradeoffs, and create consulting deliverables and enablement materials that support adoption and handoff.

Requirements

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 and 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, to support end-to-end analytics delivery.
Understanding of data-platform security and governance concepts, including access controls, least privilege, compliance, and lineage.
Strong communication skills, including the ability to present recommendations, align stakeholders, and manage expectations in a client environment.

Nice To Haves

Power Apps experience.
Direct experience with Microsoft Fabric components, including OneLake, Lakehouse, Warehouse, Data Factory in Fabric, and Real-Time Analytics/KQL databases, including platform administration, capacity planning, and standards.
Experience with Azure data-platform services such as Azure Data Factory, Synapse, Databricks, ADLS Gen2, and Key Vault.
Working knowledge of Azure architecture fundamentals across identity, networking, storage, monitoring, resiliency, and cost management.
Familiarity with AI-enablement patterns, such as preparing governed enterprise data for Azure AI Search or Microsoft Foundry, retrieval-augmented generation, or agent-based solutions; deep agent application development experience is not required.
Experience implementing CI/CD and Infrastructure as Code, including environment strategy and release management for data solutions.
Familiarity with semantic modeling and BI enablement patterns, including Power BI datasets, self-service analytics, and governance guardrails.
Current relevant Microsoft certifications, especially Fabric Data Engineer Associate (DP-700), Power BI Data Analyst Associate (PL-300), or Azure Solutions Architect Expert (AZ-305); equivalent current Microsoft credentials are also welcome.
Experience mentoring or enabling client teams.

Responsibilities

Lead client discovery to understand business goals, data landscapes, constraints, and success metrics, and translate findings into 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 data from operational systems, APIs, and third-party sources, transforming raw data into curated datasets.
Build and maintain analytics-ready data models and schemas, including enrichment, business rules, and reusable patterns.
Enable SQL, Spark/PySpark, Spark SQL, and KQL compute engines to work against shared datasets.
Prepare governed data products and reusable datasets for BI, advanced analytics, and AI use cases, including retrieval-ready data patterns where relevant.
Establish data quality practices such as validation, reconciliation, testing, and monitoring; troubleshoot failures and improve pipeline resiliency.
Optimize transformations, query performance, and pipeline execution to meet client service-level and cost objectives.
Implement logging, metrics, and operational runbooks, and support deployments, cutovers, and hypercare as needed.
Design and implement security, governance, and compliance controls, including access, least privilege, data protection, and lineage across Azure and Fabric.
Facilitate workshops and communicate architecture tradeoffs while partnering with client stakeholders, architects, analysts, and BI developers.
Produce design documents, diagrams, implementation guides, and enablement materials to support adoption and a smooth handoff.