Skills Required:

Data Architecture: In-depth knowledge and experience in designing and implementing scalable, secure, and high-performing data architectures in the cloud.

Cloud Technologies: Proficiency in cloud platforms such as Microsoft Azure,including their data services like Databricks, Azure Data Factory and other Azure Services.

Data Modernization: Expertise in modernizing legacy data systems and transitioning them to cloud-based architectures using industry best practices.

Data Integration: Strong understanding of data integration techniques, including ETL (Extract, Transform, Load) processes, data pipelines, and data streaming

using Python, Pyspark and ETL services provided by cloud providers and SQL/PLSQL

Database Technologies: Familiarity with various database technologies, both relational and non-relational, such as SQL databases, NoSQL databases,

data lakes, and data warehouses. Should have strong hands-on knowledge in Data Modelling techniques.

Data Governance: Knowledge of data governance principles and practices, including data quality, data lineage, data privacy, and compliance.

Data Security: Understanding of data security principles, including encryption, access controls, and data masking techniques.

Programming and Scripting: Proficiency in programming languages such as Python, Java, or Scala, and experience with scripting languages like SQL or Shell scripting.

Communication and Collaboration: Excellent communication and collaboration skills to effectively work with stakeholders, business users, and technical teams.

Experirence:

Be a graduate or equivalent with 12+ years of industry experience.

Responsibilities:

Collaborate with stakeholders to understand business requirements and translate them into data architecture strategies and solutions.

Design and develop scalable, secure, and high-performing data architectures in the cloud, leveraging cloud technologies and services.

Modernize legacy data systems and migrate them to cloud-based architectures, ensuring smooth transition and minimal disruption.

Collaborate with data engineers, data scientists, and other IT professionals to design and implement data pipelines, data transformation processes, and data integration solutions.

Ensure data governance principles and best practices are implemented, including data quality controls, data privacy, and compliance.

Optimize data platforms for performance, scalability, and cost efficiency, monitoring and troubleshooting any issues that may arise.

Stay updated with the latest trends and advancements in cloud technologies and data architecture, continuously enhancing knowledge and skills.

Provide guidance and mentorship to junior team members, fostering a culture of learning and growth.

Act as a subject matter expert in data architecture and cloud technologies, providing recommendations and insights to stakeholders and senior management.