Integris Group
Data Architect - Hybrid Position (Orlando, FL)
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 .
To support these initiatives, they are bringing in a
Senior Data Architect/Engineer
to establish enterprise standards for application and data architecture, partnering closely with the Solutions Architect and Tech Leads.
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. Guide enterprise data initiatives. 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: Bachelors degree in Computer Science, Information Systems, or related field (Masters preferred). Azure certifications in Data Engineering or Solution Architecture strongly preferred.
Essential Duties & Time Allocation 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%)
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 .
To support these initiatives, they are bringing in a
Senior Data Architect/Engineer
to establish enterprise standards for application and data architecture, partnering closely with the Solutions Architect and Tech Leads.
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. Guide enterprise data initiatives. 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: Bachelors degree in Computer Science, Information Systems, or related field (Masters preferred). Azure certifications in Data Engineering or Solution Architecture strongly preferred.
Essential Duties & Time Allocation 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%)