Network Transformation Lead

Role Overview:

Experienced Data Technical Lead to design, develop, and support scalable cloud-based data platforms and streaming data pipelines. The ideal candidate should possess strong expertise in Databricks, PySpark, Python, Java-based streaming technologies, GitLab CI/CD pipelines, and cloud migration initiatives.

Key Responsibilities:

• Design and develop scalable Databricks ETL/ELT pipelines (Lakeflow & LakeBase) using Azure Databricks, PySpark, and Python.
• Implement real-time and batch data ingestion frameworks using Kafka and Java-based streaming solutions.
• Develop and optimize data processing workflows in Azure Databricks.
• Integrate and manage data movement between PostgreSQL, YugabyteDB (Cassandra-based NoSQL), and cloud platforms.
• Build reusable frameworks for data ingestion, transformation, validation, and orchestration.
• Develop SQL-based data transformations, reporting datasets, and performance optimization solutions.
• Design and implement GitLab CI/CD pipelines for automated deployment, testing, and release management of Databricks notebooks, jobs, and data pipelines.
• Support Snowflake on-premises to Azure cloud migration initiatives.
• Ensure coding standards, performance tuning, monitoring, and operational stability of data pipelines.
• Develop Power BI dashboards and reports for business intelligence and analytics reporting.
• Develop API automation and integration solutions for data exchange between enterprise systems.

Required Skills:

• Strong experience in Python and PySpark development.
• Hands-on experience with Azure Databricks and databricks SQL.
• Experience in Java-based streaming and ingestion frameworks.
• Strong knowledge of Apache Kafka streaming concepts.
• Experience working with PostgreSQL databases.
• Experience with YugabyteDB or Cassandra-based NoSQL databases.
• Strong SQL development and query optimization skills.
• Hands-on experience with GitLab CI/CD pipeline development and deployment automation.
• Understanding cloud-based data engineering and distributed processing concepts.
• Experience in data migration projects, especially Snowflake on-prem to Azure cloud migration.
• Experience designing enterprise-scale data lake or lakehouse architectures.
• Knowledge of streaming architectures and real-time analytics.
• Familiarity with cloud monitoring and observability tools.

For applications and inquiries, contact:View email address on us.fitly.work