Data Architect
Listed on 2026-05-24
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IT/Tech
Data Engineer, Cloud Computing
Who We Are
At Concurrency, we embody innovation. We’re not just tech consultants; we are forward thinkers with a purpose. Our team thrives on disrupting the norm, constantly seeking the next challenge and pushing boundaries to redefine what’s achievable. Recognized as a Microsoft Solutions Partner, a Service Now Elite Partner, and recipient of multiple Partner of the Year awards, Concurrency is synonymous with excellence.
If you’re fueled by the desire to transform technology into real-world solutions, join us and unleash your potential as a change catalyst.
We’re looking for a full stack Data Architect to help take our Cloud, Data & AI Solutions team to the next level. Your focus will be on designing data‑intensive applications in Azure that align with customer business goals and helping set internal technical direction for our Cloud, Data & AI Solutions group. The ideal candidate excels at creating modern data solutions to stubborn business problems and enjoys working across the entire data stack from requirements gathering to system design, implementation, and documentation.
You thrive in early‑stage environments that provide freedom to move fast and ship new features at high velocity without compromising quality standards. You’ll work with a high‑performance engineering team and report directly to the Practice Manager, significantly influencing our technical direction and that of our customers.
- Be Yourself – Be the best version of your whole self. Your authenticity matters.
- Be Bold – Bravely and respectfully take risks and challenge the norm.
- Have a Growth Mindset – Be open to learning and apply your expertise.
- Be the Difference – Ensure that every interaction with your colleagues, clients and community improves their lives. Pay it forward.
- Assume Positive Intent – Lead with giving the benefit of the doubt.
- Lead end‑to‑end technical discovery and architecture design for complex data and analytics initiatives, translating ambiguous business goals into scalable, secure data solutions
- Architect modern data platforms on Azure, including lakehouse, streaming, and analytics architectures using services such as ADLS, Databricks, Fabric, Synapse, and related tooling
- Define and document reference architectures, design patterns, and implementation standards that are reusable across clients and engagements
- Serve as a trusted technical advisor to client stakeholders, guiding architectural decisions, tradeoffs, and roadmaps aligned to business outcomes
- Balance ideal‑state architecture with real‑world constraints, including cost, timeline, data maturity, and team skill sets
- Oversee and review solution implementations to ensure architectural integrity, performance, scalability, and security best practices
- Partner with delivery teams to resolve complex technical challenges and act as an escalation point for architecture‑related decisions and positive client sentiment
- Integrate AI‑augmented delivery practices into solution design and implementation, while exercising strong engineering judgment and governance
- Mentor engineers and senior engineers through architecture reviews, design sessions, and ongoing coaching
- Contribute to pre‑sales activities including technical discovery workshops, solution shaping, and proposal support
- Over 7 years of experience designing and delivering data solutions, with experience operating in an architecture or senior technical leadership role
- Deep expertise in modern data architectures, including lakehouse, ELT/ETL orchestration, data modeling, and analytics platforms on Microsoft Azure
- Proven ability to design scalable data solutions supporting structured, semi‑structured, and unstructured data
- Strong hands‑on experience with technologies such as Azure Data Factory/Fabric Pipelines, Databricks (PySpark), SQL, and cloud‑native data services
- Demonstrated experience leading technical discovery, requirements gathering, and architecture design in client‑facing environments
- Strong understanding of data governance, security, and compliance considerations (e.g., RBAC, data classification, lineage)
- Experience leveraging AI‑augmented delivery…
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