Data Architect

Integris Group; Orlando (FL); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading technology firm in Orlando is seeking a Senior Data Architect/Engineer to lead the design and development of enterprise data architecture. This role requires extensive experience in data engineering, strong leadership, and deep knowledge of the Azure ecosystem. Responsibilities include building scalable data frameworks, optimizing ETL pipelines, and mentoring team members. Candidates should have at least 10 years in the field and relevant educational qualifications. This position offers the chance to work in a full-time capacity with a focus on information technology in the hospitality industry.

Qualifications

• 10+ years of experience in Data Engineering and Architecture.
• Strong leadership experience with mentoring small teams.
• Deep knowledge of Azure ecosystem and ETL pipelines.

Responsibilities

• Lead design and documentation of scalable data frameworks.
• Build and optimize secure, high-performing ETL/ELT pipelines.
• Develop solutions for analytics and AI/ML use cases.

Skills

Data Engineering and Architecture

Leadership

Azure ecosystem

ETL pipelines

SQL

Data APIs

Metadata management

Programming (SQL, Python, Spark)

Containerization (Docker, Kubernetes)

Salesforce data models

Education

Bachelor’s degree in Computer Science

Azure certifications

Job description

Direct message the job poster from Integris Group

Business Challenge

The company is in the midst of an AI transformation, creating exciting opportunities for growth. At the same time, they are leading a Salesforce modernization and integrating the systems and data of their recent acquisition.

Role Overview

The Senior Data Architect/Engineer leads the design, development, and evolution of enterprise data architecture, while contributing directly to the delivery of robust, scalable solutions. This position blends strategy and hands‑on engineering, requiring deep expertise in modern data platforms, pipeline development, and cloud‑native architecture.

You Will

• Define architectural standards and best practices.
• Evaluate and implement new tools.
• Partner with data product teams, engineers, and business stakeholders to build platforms supporting analytics, reporting, and AI/ML workloads.

Day-to-Day Responsibilities

• Lead the design and documentation of scalable data frameworks: data lakes, warehouses, streaming architectures, and Azure-native data platforms.
• Build and optimize secure, high‑performing ETL/ELT pipelines, data APIs, and data models.
• Develop solutions that support analytics, advanced reporting, and AI/ML use cases.
• Recommend and standardize modern data tools, frameworks, and architectural practices.
• Mentor and guide team members, collaborating across business, IT, and architecture groups.
• Partner with governance teams to ensure data quality, lineage, security, and stewardship.

Desired Skills & Experience

• 10+ years of progressive experience in Data Engineering and Architecture.
• Strong leadership experience, including mentoring small distributed teams (currently 4 people: 2 onshore, 2 offshore; team growing to 6).
• Deep knowledge of Azure ecosystem (Data Lake, Synapse, SQL DB, Data Factory, Databricks).
• Proven expertise with ETL pipelines (including 3rd‑party/vendor integrations).
• Strong SQL and data modeling skills; familiarity with star/snowflake schemas and other approaches.
• Hands‑on experience creating Data APIs.
• Solid understanding of metadata management, governance, security, and data lineage.
• Programming experience with SQL, Python, Spark.
• Familiarity with containerized compute/orchestration frameworks (Docker, Kubernetes) is a plus.
• Experience with Salesforce data models, MDM tools, and streaming platforms (Kafka, Event Hub) is preferred.
• Excellent problem‑solving, communication, and leadership skills.

Education

• Bachelor’s degree in Computer Science, Information Systems, or related field (Master’s preferred).
• Azure certifications in Data Engineering or Solution Architecture strongly preferred.
• Data Architecture Leadership – Define enterprise‑wide strategies and frameworks (35%)
• Engineering & Delivery – Build and optimize ETL/ELT pipelines, APIs, and models (30%)
• Tooling & Standards – Evaluate new tools and support adoption of modern practices (15%)
• Mentorship & Collaboration – Mentor engineers and align stakeholders (10%)
• Governance & Quality – Embed stewardship, lineage, and security into architecture (10%)

Seniority Level

Mid‑Senior level

Employment Type

Full‑time

Job Function

Information Technology

Industries

Hospitality