Modern Data Architect (Cloud, AI & Analytics)

Modern Data Architect

Job Summary
We are seeking a Modern Data Architect to design and deliver next-generation, cloud-native data platforms that enable advanced analytics, AI/ML, and digital transformation initiatives. This role will drive data architecture strategy, build scalable and secure data solutions, and collaborate with cross-functional teams to unlock business value through data.

Key Responsibilities

• Design, develop, and maintain modern data platforms and architectures that support enterprise data and analytics needs.
• Create and optimize data pipelines, ETL/ELT processes, and real-time streaming solutions for large-scale data environments.
• Architect cloud-native data ecosystems using platforms such as Azure, AWS, or GCP.
• Develop logical and physical data models for structured, semi-structured, and unstructured data sources.
• Implement data governance, metadata management, master data management, and data quality frameworks.
• Collaborate with business stakeholders, product owners, and engineering teams to translate requirements into scalable data solutions.
• Evaluate, recommend, and implement modern data technologies, tools, and frameworks aligned with enterprise strategy.
• Ensure data security, compliance, reliability, and performance across data platforms.
• Drive adoption of modern architecture patterns such as Data Mesh, Data Fabric, Data Virtualization, and Lakehouse architectures.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• At least 5 years of experience in Data Architecture, Data Engineering, or related roles.
• Strong experience with cloud platforms such as Azure, AWS, or GCP.
• Hands-on expertise with modern data platforms including Databricks, Snowflake, Synapse, BigQuery, or Redshift.
• Experience with ETL/ELT tools and frameworks such as Azure Data Factory, Airflow, dbt, or AWS Glue.
• Knowledge of real-time data processing and streaming technologies such as Kafka and Spark Structured Streaming.
• Strong understanding of data modeling, data governance, metadata management, and data quality practices.
• Experience integrating data platforms with analytics, AI, and machine learning solutions.
• Excellent communication and stakeholder management skills.

Preferred Skills

• Experience with DataOps, DevOps, and CI/CD practices for data pipelines.
• Familiarity with data catalog and governance tools such as Collibra, Alation, or Microsoft Purview.
• Exposure to AI/ML platforms and modern analytics ecosystems.
• Experience leading data modernization and digital transformation initiatives.