Data Architect

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, Py. Spark, 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, Py. Spark, 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.