Solution Cloud Data Architect

6 days ago

Bengaluru Karnataka, India CIGNEX Datamatics Full time

**Location** : Hybrid, Bangalore

**Technology** : Azure Datalakes, Databricks, ETL

**Responsibilities**:

- Develop and deliver detailed technology solutions through consulting project activities.
- Evaluate and recommend emerging cloud data technologies and tools to drive innovation and competitive advantage, with a focus on Azure services such as Azure Data Lake, Azure Synapse Analytics, and Azure Databricks.
- Lead the design and implementation of cloud-based data architectures using Azure and Databricks to support the company's strategic initiatives and exploratory projects.
- Collaborate with cross-functional teams to understand business requirements, architect data solutions, and drive the development of innovative data platforms and analytics solutions.
- Define cloud data architecture standards, best practices, and guidelines to ensure scalability, reliability, and security across the organization.
- Design and implement data pipelines, ETL processes, and data integration solutions to ingest, transform, and load structured and unstructured data from multiple sources into Azure data platforms.
- Provide technical leadership and mentorship to junior team members, fostering a culture of collaboration, continuous learning, and innovation in cloud data technologies.
- Collaborate with Azure and Databricks experts within the organization and the broader community to stay abreast of the latest developments and best practices in cloud data architecture and analytics.

**Qualifications**:

- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
- Proven experience (12+ years overall and 2+ years as Architect) as a Cloud Data Architect or a similar role, with a focus on delivering detailed technology solutions implementing cloud-based data solutions using Azure and Databricks.
- Conceptual knowledge of MS Fabric
- In-depth knowledge of cloud data architecture principles, methodologies, and best practices, with hands-on experience in Azure cloud services and Databricks. Expertise in modernizing legacy data systems and transitioning them to cloud-based architectures using industry best practices.
- Strong understanding of data integration techniques, including ETL (Extract, Transform, Load) processes, data pipelines, and data streaming using Python, Kafka for streams, Pyspark, DBT, and ETL services provided by cloud providers and SQL/PLSQL
- Familiarity with machine learning and advanced analytics tools and frameworks.
- Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and influence decision-making at all levels of the organization.

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