Architect - Data Platform Engineer – Transformation & Modernization

ob Overview: A Data Platform Engineer to be a key player in our transformation and modernization programs, leading the migration of applications from legacy systems to Azure-based architectures. This role involves designing, implementing, and optimizing scalable, cloud-native data solutions using Databricks, Azure DevOps (ADO), and Agile development methodologies.

As an active contributor to code development, you will help drive automation, operational excellence, and data quality across our platforms. You will collaborate with data science and product teams to create solutions that enhance our data-driven decision-making capabilities.

Responsibilities:

• Lead the migration and modernization of data platforms, moving applications and pipelines to Azure-based solutions.

• Actively contribute to code development in projects and services.
• Manage and scale data pipelines from internal and external data sources to support new product launches and ensure high data quality.
• Develop automation and monitoring frameworks to capture key metrics and operational KPIs for pipeline performance.
• Implement best practices around systems integration, security, performance, and data management.
• Collaborate with internal teams, including data science and product teams, to drive solutioning and proof-of-concept (PoC) discussions.
• Develop and optimize procedures to transition data into production.
• Define and manage SLAs for data products and operational processes.
• Prototype and build scalable solutions for data engineering and analytics.
• Research and apply state-of-the-art methodologies in data and Platform engineering.
• Create and maintain technical documentation for knowledge sharing.
• Develop reusable packages and libraries to enhance development efficiency.

Qualifications:

• Bachelor’s degree in Computer Science, MIS, Business Management, or related field

• 10 + years’ experience in Information Technology
• 4 + years of Azure, AWS and Cloud technologies
• Experience in data platform engineering, with a focus on cloud transformation and modernization.
• Strong knowledge of Azure services, including Databricks, Azure Data Factory, Synapse Analytics, and Azure DevOps (ADO).
• Proficiency in SQL, Python, and Spark for data engineering tasks.
• Hands-on experience building and scaling data pipelines in cloud environments.