We are seeking a highly experienced Data Architect to design and lead modern, scalable, and secure cloud data platforms that power analytics, reporting, and AI-driven decision-making for enterprise customers.
This is a senior, impactful role for someone who can combine deep technical expertise with strong stakeholder engagement shaping data strategy while guiding engineering teams to deliver robust, enterprise-grade solutions.
What you'll do:
- Lead end-to-end architecture for cloud-based data ecosystems, including lakehouse and enterprise analytics platforms
- Translate business needs into scalable architectural designs, technical roadmaps, and governance frameworks
- Architect and implement Databricks solutions using Unity Catalog, Delta Lake, Databricks SQL, and Workflows
- Define and enforce data modelling standards across relational, dimensional, and lakehouse architectures
- Design and oversee ETL/ELT frameworks, metadata strategies, and reusable transformation standards
- Establish best practices for data ingestion, quality, lineage, cataloging, and MDM (preferably Profisee)
- Partner with engineering teams to ensure performance, security, and architectural consistency
- Build cloud-native reference architectures using Azure services such as ADF, ADLS, Synapse, and Stream Analytics
- Collaborate with executive stakeholders to define data governance, taxonomy, and metadata strategies
- Mentor and guide junior engineers through design reviews and technical decision-making
Minimum Qualifications:
- Bachelor's degree in Computer Science, Engineering, MIS, or related field
- 12+ years total experience, with 3+ years in data architecture
- 3+ years hands-on Databricks experience (Unity Catalog, Delta Lake, SQL, Workflows)
- Strong expertise in Python, Apache Spark, and distributed data processing
- Advanced SQL skills, including performance tuning and optimization
- Proven experience designing lakehouse architectures and cloud data platforms
- Hands-on experience with Azure Data Services (ADF, ADLS, Azure SQL, Synapse, Stream Analytics or Fabric)
- Deep understanding of data modelling (3NF, Kimball, Inmon) and enterprise data warehousing
- Prior consulting experience with enterprise clients
- Familiarity with CI/CD and IaC tools (Terraform, ARM, Bicep)
Preferred Skills:
- Experience building automated CI/CD pipelines and environment strategies
- Exposure to Microsoft Fabric or other modern analytics platforms
- Experience with Big Data technologies (HDFS, Hive, MapReduce)
- Familiarity with NoSQL systems (Cassandra, MongoDB, HBase, CouchDB)
- Experience with BI tools such as Power BI, Tableau, Qlik, or Cognos
