Summary
Our talented Data & AI Practice is made up of globally recognized experts - and there's room for more analytical and ambitious data professionals. If you're passionate about helping clients make better data-driven decisions to tackle their most complex business issues, let's talk. Take your skills to a new level and launch a career where you can truly do what matters.
As a Data Platform Architect within our Data & AI Practice, you'll leverage a client-centric approach to translate our client's business strategy into solutions and services that lead to successful, impactful outcomes.You'll engage in solutioning and support on the most strategic opportunities, intervene in high-risk complex deliveries, and contribute toshape the strategic direction around data architecture.
Together we do what matters.
Key Responsibilities
- Design, document, and maintain end-to-end data platform architectures, ensuring alignment with enterprise data strategy and business goals.
- Lead the development and implementation of scalable, secure, and high-performance data solutions across cloud and on-premises environments.
- Define and enforce data architecture standards, best practices, and governance frameworks for data engineering and warehousing initiatives.
- Collaborate with stakeholders, including business leaders, data engineers, and solution architects, to translate requirements into robust data platform designs.
- Oversee the integration of data from multiple sources, ensuring data quality, lineage, and compliance with security and privacy regulations.
- Guide the adoption of modern data platform technologies (such as Azure, Databricks, Microsoft Fabric), and medallion/layered architectures for data lakes and warehouses.
- Mentor and onboard data engineering teams, providing architectural direction and technical leadership throughout project lifecycles.
- Participate in architecture governance forums and contribute to the continuous improvement of data platform capabilities.
Qualifications
Skills and experiences
- 1012 years of experience in data engineering, data warehousing, or related fields, with a strong track record of architecting enterprise-scale data platforms.
- Deep expertise in data modeling, database design, and big data architectures (relational, NoSQL, cloud-native, and hybrid).
- Proficiency in ETL/ELT techniques, data integration, and orchestration tools (such as Azure Data Factory, Databricks, Airflow).
- Hands-on experience with cloud platforms (Azure, AWS, GCP), data lake and warehouse solutions, and modern analytics stacks.
- Strong programming skills in Python, SQL, and familiarity with Spark, Hadoop, or similar frameworks.
- Knowledge of data governance, security, compliance, and data lifecycle management.
- Experience leading cross-functional teams, managing stakeholders, and driving architectural decisions in complex environments.
- Excellent communication, documentation, and presentation skills, with the ability to influence technical and business audiences.
