Data Solution Architect

Role Overview

We are looking for an experienced Data Solution Architect with strong expertise in data architecture, cloud data platforms, data engineering, and enterprise data solutions. The ideal candidate will be responsible for designing scalable, secure, and high-performance data architectures, translating business requirements into technical solutions, and guiding data engineering teams in implementing robust data platforms.

The candidate should have a strong understanding of modern data ecosystems, data integration, data warehousing, ETL/ELT pipelines, and cloud-based data solutions.

Key Responsibilities

• Design and implement end-to-end data architecture solutions aligned with business and enterprise requirements.
• Define data platform architecture, data models, data integration patterns, and data processing frameworks.
• Architect scalable data pipelines using batch and streaming technologies.
• Design modern data platforms using data lakes, data warehouses, lakehouse architectures, and cloud-native services.
• Evaluate and recommend suitable technologies, tools, and platforms based on business needs and technical requirements.
• Establish data governance, data quality, metadata management, data security, and compliance standards.
• Collaborate with business stakeholders, data engineers, data analysts, and cloud teams to define solution requirements.
• Develop architecture diagrams, high-level designs (HLDs), low-level designs (LLDs), and technical documentation.
• Optimize data platform performance, scalability, reliability, and cost efficiency.
• Provide technical leadership and architectural guidance to data engineering teams throughout implementation and deployment.
• Define best practices for CI/CD, infrastructure automation, monitoring, and operational support of data platforms.

Required Technical Skills

• Strong expertise in data architecture, data engineering, and enterprise data platform design.
• Hands-on experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• Strong understanding of data warehousing, data lakes, lakehouse architecture, and ETL/ELT processes.
• Experience with SQL, Python, data modelling, and distributed data processing.
• Knowledge of Apache Spark, PySpark, Databricks, or equivalent big data technologies.
• Experience with data integration and orchestration tools such as Azure Data Factory, AWS Glue, Apache Airflow, or equivalent.
• Understanding of relational and NoSQL databases, data modelling, and data optimization techniques.
• Knowledge of data governance, security, access controls, data quality, and metadata management.
• Experience designing scalable, reliable, and cost-effective data solutions.

Preferred Skills

• Experience with Microsoft Fabric, Snowflake, Delta Lake, dbt, or equivalent modern data platforms.
• Knowledge of real-time data processing, streaming, and event-driven architectures.
• Experience with data lakehouse patterns, medallion architecture, and enterprise data integration.
• Familiarity with DevOps, CI/CD, infrastructure as code, and automated data deployments.
• Relevant cloud or data architecture certifications.