Description

Design and optimize large-scale data architectures and processing pipelines in Azure and multi-cloud environments.

Responsibilities

• Develop and execute ETL processes for data extraction, transformation, and loading into warehouses and data lakes.
• Architect data warehousing solutions using Azure Synapse Analytics for efficient querying and reporting.
• Construct seamless data pipelines across Azure services using Azure Data Factory, Databricks, and SQL Server Integration Services.
• Manage large data volumes leveraging the Hadoop ecosystem, including MapReduce, Spark, and Hive.
• Optimize query performance, data processing speed, and resource utilization within Azure and Hadoop clusters.

Required Skills

• 6+ years of experience in data engineering, architecture, and implementation of large-scale data solutions.
• Advanced proficiency in SQL and NoSQL databases.
• Hands-on experience with Azure Synapse, Azure Data Factory, and Databricks.
• Experience with SQL Server and the Hadoop ecosystem (Spark, Hive, MapReduce).
• Ability to code custom applications using Java or Python.
• Experience integrating cross-cloud data with AWS and GCP services.
• Strong knowledge of designing data models, data structures, and algorithms.

Preferred Skills

• Relevant certifications in Azure, AWS, or GCP.

Key Skills

Education

Any Graduate