Data Architect Manager

360training

10h•Remote

About The Position

360training is looking for a hands-on data platform leader to help modernize our data architecture and build the foundation for AI, analytics, and trusted reporting. This role will help design and deliver a modern cloud data platform, with an emphasis on the Azure ecosystem, while bringing strong experience from modern platforms such as Microsoft Fabric, Databricks, Snowflake, Synapse, AWS, or similar technologies. The right candidate is both technical and practical: someone who can set architecture patterns, guide engineers, improve legacy data environments, and personally dive into implementation details when needed. This is not a traditional BI reporting role. We need someone who understands modern data platforms, AI-ready data architecture, medallion or lakehouse design patterns, governance, schema evolution, and how to create reliable data products that can support reporting, analytics, applications, data science, and AI-enabled workflows.

Requirements

7+ years of experience in data engineering, data architecture, analytics engineering, or cloud data-platform delivery.
Hands-on experience building or modernizing cloud data platforms using Azure, Microsoft Fabric, Databricks, Snowflake, Synapse, AWS, or similar technologies.
Strong understanding of lakehouse, medallion, data warehouse, and data modeling patterns, including when dimensional modeling is useful and when it should not drive the entire architecture.
Experience with tools such as Azure Data Lake, Azure Data Factory, Microsoft Fabric, Databricks, Synapse, Power BI, Purview, dbt, Snowflake, SQL, Python, Delta Lake, or similar technologies.
Practical experience with schema evolution, metadata-driven ingestion, pipeline automation, data quality checks, lineage, security, access control, documentation, and observability.
Experience preparing enterprise data for AI-enabled use cases, such as governed data access, semantic consistency, search, summarization, data science, predictive analytics, or agent-based workflows.
Strong SQL skills and the ability to design, review, debug, and optimize data pipelines, models, and transformations.
Experience improving legacy data environments with complex pipelines, inconsistent definitions, fragmented reporting logic, Power BI dependencies, stored procedures, or manual processes.
Ability to lead technical execution while communicating clearly with business and technology stakeholders.
Hands-on leadership style with the ability to set standards, guide a small team, and still build, review, troubleshoot, and deliver directly when needed.

Responsibilities

Lead the design and implementation of modern cloud data-platform capabilities, with a primary focus on Azure-based architecture and delivery.
Establish practical patterns for ingestion, transformation, medallion-style data layers, data quality, lineage, governance, security, testing, and consumption.
Build scalable approaches for onboarding new sources, tables, columns, attributes, and acquired-company data without creating brittle one-off solutions.
Create governed data products that can support Power BI, analytics, operational reporting, data science, AI search, summarization, predictive analytics, and future agent-based workflows.
Move business logic, metric definitions, and reusable transformations into governed, version-controlled platform layers rather than scattered reports, spreadsheets, scripts, or stored procedures.
Partner with BI, analytics, engineering, product, finance, and business teams to improve data trust, reporting reliability, platform usability, and delivery speed.