Data Architect (100% Onsite)

Luna Data Solutions is seeking a Data Architect for a full-time, direct hire role based in Fort Wayne IN.

• Compensation package includes base salary, quarterly bonus, profit sharing bonus once a year
• 100% onsite
• Will consider candidates outside of Fort Wayne, IN if willing to relocate - relo assistance available

This position will act as the primary technical leader for a strategic enterprise data platform initiative. The selected individual will be responsible for shaping and delivering a greenfield scalable, company-wide data platform that underpins enterprise reporting, analytics, and advanced AI/ML capabilities.

Initially, this role will function as a senior-level individual contributor with extensive hands-on responsibilities related to platform design and implementation. Over time, as the platform and data organization expand, the role is expected to evolve into a broader leadership capacity. Ideal candidates will bring a balance of architectural vision and strong execution skills.

Key Responsibilities

• Own the end-to-end design and development of the enterprise data platform, including technology selection, reference architecture, and foundational design standards.
• Define and implement approaches for ingesting data from various divisional systems—largely on-premises SQL Server—into a centralized, Azure cloud-based platform, ensuring security, scalability, and reliability.
• Establish and enforce enterprise-level standards and best practices for data engineering within the shared platform environment.
• Collaborate with divisional IT teams to integrate their data into the enterprise platform, offering guidance and support while allowing divisions to retain ownership of their data assets.
• Provide hands-on engineering support to business units lacking dedicated data engineering resources, with an eventual transition plan as internal capabilities expand.
• Design and implement platform-wide security, governance, and access management frameworks.
• Ensure the platform is architected to enable advanced analytics, including artificial intelligence and machine learning workloads.
• Define best practices for environments, CI/CD pipelines, cost optimization, and operational monitoring.
• Lead technical evaluations of vendors and tools, including proof-of-concept initiatives and final technology recommendations.
• Mentor and guide data engineers and analysts across business units in using the platform effectively.
• Communicate technical architecture, risks, and trade-offs clearly to executive and non-technical stakeholders, aligning solutions with business goals.

Required Qualifications

• 10 years of experience delivering enterprise-grade software solutions in production environments.
• At least 4 years of hands-on experience in Azure data engineering, data warehousing, or data architecture.
• Proven track record of leading and delivering large-scale or greenfield enterprise data platforms across multiple systems or business areas.
• Experience designing hybrid architectures that integrate on-premises systems with cloud-based data platforms.
• Familiarity with multiple cloud data technologies and the ability to evaluate and recommend appropriate solutions.
• Strong experience within the Microsoft data and analytics ecosystem.
• Solid technical skills in SQL, at least one programming language commonly used in data engineering, and modern data platform practices.
• Experience working with diverse data sources, including ERP and operational systems, across multiple business units.
• Understanding of data governance, security, and compliance considerations in enterprise environments.
• Strong communication skills with the ability to engage both technical teams and executive audiences.
• Ability to influence across a decentralized organization and build alignment without direct authority.
• Bachelor’s degree in a relevant field or equivalent experience.

Preferred Qualifications

• Background in manufacturing, industrial, or asset-intensive industries.
• Experience integrating MES, historian, or shop-floor systems alongside ERP or financial platforms.
• Experience designing platforms that support AI/ML and large language model use cases.
• Experience mentoring or leading distributed data engineering teams.
• Experience implementing data governance in decentralized organizational structures.