Unison Group Hiring! Full Time Technical Manager- Data Project Manager in - Ricebowl

 Lead and manage large-scale Data Engineering and Data Modernization projects.Hands-on experience in managing Data projects end-to-end — effort estimation, scoping, project plan, timelines, team allocation, stakeholder management

 Drive end-to-end delivery of Data Lake build and migration initiatives.Hands-on experience with modern Data technologies like PySpark, SQL, CML, Python on any cloud; preferred GCP

 Lead PySpark migration and optimization projects, ensuring performance and scalability. Transform business requirements into Data solutions, manage risks, issues and dependencies

 Design and implement modern data architectures, including Data Lakes, Data Warehouses, and Lakehouse solutions.

 Collaborate with business stakeholders, architects, and engineering teams to define data strategies and roadmaps.

 Provide technical leadership and mentorship to Data Engineers and Developers.

 Ensure best practices around:

• Data governance
• Data quality
• Security and compliance
• Performance optimization

 Lead data platform modernization initiatives across cloud environments.

 Review solution designs, architecture documents, and implementation approaches.

 Manage project planning, resource allocation, risks, and delivery timelines.

 Drive Agile delivery and ensure successful project execution.

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  Hands-on experience in managing Data projects end-to-end — effort estimation, scoping, project plan, timelines, team allocation, stakeholder management
• Hands-on experience with modern Data technologies like PySpark, SQL, CML, Python on any cloud; preferred GCP
• Transform business requirements into Data solutions, manage risks, issues and dependencies
• Proven experience in delivering:
• • Data Lake implementation projects
  • Data Lake migration programs
  • PySpark migration projects
  • Large-scale data transformation initiatives

Technical Skills

• Strong expertise in:
• • Python
  • PySpark
  • Spark SQL
  • SQL
  • ETL/ELT frameworks
• Experience with:
• • Hadoop ecosystem
  • Data Lakes and Lakehouse architectures
  • Distributed data processing frameworks
• Strong understanding of:
• • Data modeling
  • Data integration patterns
  • Batch and real-time processing
• Experience with cloud platforms such as:
• • AWS
  • Azure
  • GCP
• Hands-on experience with:
• • Data migration strategies
  • Performance tuning and optimisation
  • CI/CD and DevOps practices for data platforms

Preferred Skills

• Experience with:
• • Databricks
  • Delta Lake
  • Apache Airflow
  • Kafka
  • Snowflake
  • Kubernetes and Docker
• Experience in Banking, Financial Services, or other large enterprise environments.
• Exposure to data governance and data quality frameworks.