Description

You will design and implement large-scale data and analytics architectures across hybrid cloud and on-premises environments.

Responsibilities

• Design, validate, and implement data architectures across hybrid infrastructure, including on-cloud to on-premises migrations.
• Set up data lakes and analytical environments to support large-volume data projects.
• Build data pipelines, ingestion processes, integrations, and traditional data warehouses or datamarts.
• Align business process initiatives and strategies with planned data engineering and analytics architecture through management consultation.
• Serve as the primary technical lead for critical programs, resolving integration issues and managing tool implementations.

Required Skills

• 14+ years of IT experience.
• 12+ years in Data Engineering, Data Modeling, Data Warehousing, MDM, RDM, Data Lineage, Data Governance, and Metadata Management.
• 10+ years defining Data & Analytics architecture for large-volume projects on-prem and in the cloud, preferably AWS.
• Expertise in building processes for data transformation, structures, metadata, dependency, and workload management.
• Proficiency with Python, PySpark, Kafka, APIs, Talend, and BODS.
• Strong experience with relational SQL and NoSQL databases.
• Expertise in data modeling using tools such as Erwin or ER Studio.
• Experience with message queuing, stream processing, and scalable big data stores.
• Any Graduate degree.

Preferred Skills

• 7+ years collaborating with Agile teams.
• Experience with visualization tools like QlikView, Qlik Sense, or Tableau.

Key Skills

Education

Any Graduate