Enterprise Data Platform Architect & Strategic Technology Consultant at SereneAid

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

03 Mar, 26

Salary

0.0

Posted On

03 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, Cloud Data Platforms, Azure, Databricks, Delta Lake, DataOps, AI Capabilities, Governance, Security, Compliance, ETL Workloads, Performance Tuning, Automation, Mentorship, Data Engineering, Platform Optimization

Industry

Home Health Care Services

Description

An enterprise technology division is seeking a highly skilled consultant to lead the enhancement, sustainment, and strategic development of a large-scale Azure-based data management platform. The role focuses on defining technology roadmaps, advancing data modernization initiatives, and enabling key data, analytics, and AI capabilities across the organization. The consultant will guide how data is ingested, governed, transformed, and delivered at an enterprise level ensuring scalability, consistency, and trusted data use for integrations, analytics, reporting, operational decision-making, and AI workloads. This position requires strong strategic insight paired with hands-on experience in cloud-native data architecture, Azure, Databricks, Delta Lake, DataOps, and platform optimization. Tasks Strategic Leadership & Collaboration • Develop the strategic vision and multi-year roadmap for the enterprise data platform. • Collaborate closely with service owners and senior stakeholders to prioritize capabilities and influence long-term modernization efforts. • Translate business and organizational goals into actionable platform strategies, shaping enterprise architecture, governance, and AI readiness. • Promote enterprise adoption through standardized data products, reusable frameworks, and self-service capabilities. ** Technical Architecture & Engineering Execution** • Architect and implement cloud-native data solutions using Azure and Databricks, including Delta Lake, Unity Catalog, and Medallion architectures. • Lead the design and development of scalable data ingestion, transformation, and orchestration pipelines using Databricks, Azure Data Factory, Event Hub, Functions, and APIs. • Define and enforce governance, security, and compliance frameworks including RBAC/ABAC, encryption practices, and secure networking models. • Implement DataOps practices and CI/CD automation for Databricks workflows and Azure data pipelines. • Optimize performance, reliability, and cost efficiency across Databricks clusters, ETL workloads, and Azure resources. ** AI Enablement & Automation** • Identify opportunities for AI-driven automation such as automated pipeline generation, intelligent observability, anomaly detection, and generative code scaffolding. • Lead proofs of concept and assessments of new Azure, Databricks, and AI capabilities, and recommend adoption paths. ** Team Enablement & Mentorship** • Mentor and guide data engineering and platform teams to ensure strong technical standards and continuous improvement. • Provide architectural expertise to teams building data products, analytics solutions, and AI workloads using the enterprise data platform. Requirements Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (Master’s preferred). 8–12+ years of experience in data architecture, cloud data platforms, or enterprise data engineering. Proven experience leading large-scale data platform modernization or cloud transformation initiatives. Strong background in Azure and Databricks ecosystem, including: Delta Lake, Medallion architecture Unity Catalog, schema management Azure Data Factory, Event Hub, Functions, Key Vault Cluster configuration, performance tuning, and optimization Hands-on experience designing cloud-native data solutions and scalable pipelines.

Responsibilities

The consultant will lead the enhancement and strategic development of a large-scale Azure-based data management platform. This includes defining technology roadmaps and enabling key data, analytics, and AI capabilities across the organization.