Data Architect

PALO IT

Palo (MI)

On-site

USD 140,000 - 200,000

Full time

10 days ago

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Benefits offered by this job

Stimulating working environments

International mobility

Internal R&D projects (Gen-e2)

Knowledge sharing

PALO IT Academy training

Entrepreneurship & intrapreneurship

Job summary

PALO IT is seeking a seasoned Data Architect to lead the design, evolution, and optimization of data architecture for scalable, secure solutions. You will collaborate with data engineers, analytics teams, and IT leadership to drive data strategies that power decision-making and digital transformation.

Responsibilities include defining enterprise data models, governance policies, and data integration patterns.

Qualifications

10+ years of experience in data engineering.
3+ years designing cloud-based data architectures (Azure, AWS, or GCP).
2+ years in data architecture, enterprise data modeling, or data governance.
Led data model design for Data Warehouse, Data Lake, or Lakehouse.
Experience with Data Mesh and cataloging tools (Purview, Unity Catalog) is a plus.

Responsibilities

Define, evolve, and document data architecture aligned with business and IT strategy.
Design enterprise data models (conceptual, logical, physical) with standards.
Assess data technologies (Data Lake, Lakehouse, Mesh, Warehouse) for needs.
Define policies for data governance, quality, privacy, cataloging, and lineage.
Lead adoption of metadata management and data discovery tools.
Ensure compliance with data regulations and security requirements.
Architect data integration solutions (ETL/ELT, real-time and batch).
Promote data models and best practices across teams.
Translate business needs into scalable data solutions.

Skills

Cross-functional Communication

Systemic Thinking

Technical Leadership

Data Modeling

Data Governance

Data Architecture

Cloud Data Platforms

SQL

Python (architectural level)

Terraform / IaC

Education

Bachelor's degree in a relevant field

Tools

Azure Synapse

Azure Data Lake Gen2

Purview

Unity Catalog

Cosmos DB

Azure Data Factory

Azure Databricks

Terraform

Azure DevOps

Job description

Who We Are

Building the AI-first frontier enterprise.

We are a global technology consultancy with a trademarked, AI-first approach Gen‑e2™. It redefines how enterprises build digital products and transform their organizations with AI. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

We are small enough to care locally, big enough to deliver globally (10 countries, 450+ experts from 50+ nationalities)
We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.
We are robust and resilient (100% independent, 0 debt, founded 2009)
We are AI-native professionals who invest in what we believe and work as a collective intelligence

We are positive, courageous and deliver at the leading edge.

Your Role

As a Data Architect, you will take a leading role in designing, evolving, and optimizing data architecture for innovative, scalable, and secure solutions. You will collaborate closely with data engineers, analytics teams, business stakeholders, and IT leadership to deliver data strategies that power decision‑making and digital transformation.

Key Responsibilities

Strategy & Architecture

Define, evolve, and document the organization’s data architecture aligned with business and IT strategy.
Design enterprise data models (conceptual, logical, and physical), establishing naming conventions and modeling standards.
Assess and recommend data technologies (Data Lake, Lakehouse, Mesh, Warehouse) based on evolving business needs.

Governance, Privacy & Quality

Define policies and standards for data governance, quality, privacy, cataloging, and lineage.
Lead adoption of metadata management and data discovery tools across teams.
Ensure compliance with internal and external data regulations and security requirements.

Data Integration & Design

Architect data integration solutions (ETL/ELT, real‑time and batch pipelines).
Ensure interoperability across domains, sources, and consumers using principles such as Data Mesh.
Define integration patterns and data federation frameworks to deliver a 360° data view.

Collaboration & Leadership

Act as a technical reference in data architecture, guiding engineering, analytics, and business teams.
Promote adoption of data models, standards, and best practices across the organization.
Translate business needs into scalable data solutions and facilitate technical‑business alignment.

Who You Are

Education

Bachelor’s degree in Mechatronics Engineering, Applied Mathematics, Software Engineering, Computer Science, or related fields.

Preferred Certifications

Microsoft Certified, Azure Data Engineer Associate, or relevant cloud and data architecture certifications.

Required Experience

10+ years of experience in Data engineer
3+ years designing cloud‑based data architectures (Azure, AWS, or GCP).
2+ years in data architecture, enterprise data modeling, or data governance.
Led data model design (relational, multidimensional, non‑relational) for Data Warehouse, Data Lake, or Lakehouse architectures.
Participated in multi‑source data integration projects (on‑premise, cloud, external sources).In‑depth knowledge of data governance frameworks including quality, cataloging, privacy, and compliance.
Experience with modern architectures (Data Mesh, Lakehouse) and cataloging tools (Purview, Unity Catalog) is a plus.

Technical Expertise

Data Modeling: Conceptual, logical, physical modeling; normalization; relational and non‑relational design.
Architectures: Data Warehouse, Data Lake, Lakehouse, Data Mesh.
Governance: Data lineage, quality, privacy, RBAC, metadata management.
Platforms: Azure Synapse, Azure Data Lake Gen2, Purview, Unity Catalog, Cosmos DB.
Data Integration: Azure Data Factory, API Management, integration patterns, Azure Databricks.
Infrastructure as Code (IaC): Terraform, Azure DevOps (preferred).
Languages & Tools: SQL, Python (architectural level), JSON, Java, Scala.
CI/CD: Git, Sonar, DevOps best practices.

Leadership & Soft Skills

Systemic Thinking: Designs modular, scalable, and integrated architectures.
Cross‑functional Communication: Translates technical and business requirements clearly and effectively.
Reuse Mindset: Focuses on creating shareable and scalable components.
Technical Leadership: Influences technical direction and decision‑making across teams.
Complexity Management: Solves high‑impact, large‑scale technical challenges.
Product & Platform Mindset: Designs with the data consumer experience in mind.
Curiosity & Continuous Learning: Stays ahead of tech trends and promotes innovation.

More About PALO IT

Our clients include some of the world’s most successful companies. We collaborate with leading enterprises, next‑generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.

What We Offer