Zennify

Data Engineer

• Lead the design and implementation of modern and scalable enterprise data solutions for clients in the financial services industry.
• Architect scalable Data Lake, Lakehouse, and Data Mesh solutions using Azure, AWS, Snowflake, Databricks, and related platforms.
• Define enterprise data models using dimensional modeling, 3NF, Kimball, Data Vault methodologies.
• Assess legacy core banking systems and design modernization strategies aligned to target-state architecture.
• Establish scalable architectural patterns that support analytics, reporting, AI/ML, and distributed data products.
• Design scalable batch, streaming, API-based, and CDC-driven data pipelines.
• Lead ETL/ELT architecture and optimization using modern orchestration and transformation frameworks (e.g., PySpark, SQL, Scala, Delta Lake).
• Define and contribute to enterprise data governance frameworks including MDM, metadata management, lineage, and data quality standards.
• Design role-based access control, encryption, and regulatory compliance solutions (e.g., banking regulations, GDPR, HIPAA).
• Incorporate data observability practices including monitoring, logging, and alerting to ensure reliability and quality.
• Define and align domain-oriented data product operating models across key business domains.
• Partner with Data Product Owners and business stakeholders to align requirements, priorities, and value realization.
• Establish scalable processes that accelerate data product development while maintaining governance and quality standards.
• Serve as architectural lead in client-facing engagements, articulating strategy and technical value.
• Collaborate with sales and delivery teams to scope solutions and define engagement approaches.
• Mentor technical teams and promote best practices in architecture, engineering, and deployment.
• Monitor progress during project execution, identifying risks and ensuring alignment with architectural principles and client objectives.

Senior Data Architect