Role Overview
We are looking for an experienced Data Architect with strong expertise in Databricks and cloud-based data platforms across Azure, AWS, or Google Cloud Platform (GCP). The ideal candidate will be responsible for designing scalable, secure, high-performance data architectures and modern lakehouse solutions that support enterprise data engineering and analytics requirements.
The candidate should have a strong understanding of data modelling, data integration, cloud architecture, data governance, and performance optimization, along with the ability to translate business requirements into robust technical solutions.
Key Responsibilities
- Design and implement scalable, secure, and cost-effective data architectures using Databricks on Azure, AWS, or GCP.
- Define end-to-end lakehouse architecture, including data ingestion, transformation, storage, processing, and consumption layers.
- Develop architecture standards and best practices for data engineering, data modelling, data integration, and platform design.
- Leverage Databricks capabilities, including Delta Lake, Unity Catalog, and the Medallion Architecture, wherever appropriate.
- Design and optimize batch and streaming data pipelines using Apache Spark, PySpark, SQL, and related technologies.
- Establish data governance, security, access control, data quality, metadata management, and lineage practices.
- Collaborate with data engineers, analytics teams, business stakeholders, and cloud/platform teams to deliver reliable data solutions.
- Identify and resolve architectural challenges related to scalability, performance, reliability, and cloud cost optimization.
- Evaluate existing data platforms and recommend modernization, migration, and optimization strategies.
- Document architecture designs, technical standards, data flows, and implementation guidelines.
Required Skills and Qualifications
- Strong experience in data architecture, data platform design, or enterprise data engineering.
- Hands-on experience with Databricks and cloud-based data platforms.
- Strong expertise in at least one cloud platform: Microsoft Azure, AWS, or GCP.
- Solid understanding of lakehouse architecture, Delta Lake, and the Medallion Architecture.
- Proficiency in SQL and practical knowledge of Python, PySpark, and Apache Spark.
- Experience designing data models, data pipelines, and data integration solutions.
- Understanding of data governance, security, access management, data quality, and metadata management.
- Experience with performance tuning, scalability, reliability, and cost optimization of data platforms.
- Ability to translate business and technical requirements into scalable architectural solutions.
- Strong communication, problem-solving, stakeholder management, and technical documentation skills.
Preferred Qualifications
- Experience with Databricks Unity Catalog, Delta Live Tables / Lakeflow Declarative Pipelines, and workflow orchestration.
- Knowledge of dimensional modelling, Data Vault, enterprise data modelling, or similar approaches.
- Experience with cloud-native storage, data services, and orchestration tools.
- Exposure to CI/CD, infrastructure automation, monitoring, and data platform operational practices.
- Experience in data warehouse modernization, cloud migration, or large-scale data platform transformation.
