Lead Data Engineer

1 week ago

Providence, RI, United States Cynet Systems Full time
Job Description:

Required Skills:
  • 12+ years of experience with expertise in solutioning Data Warehouse platform, architecting designing complex.
  • Data Analytics projects Experience in modernization migration from legacy.
  • Data Warehouse platform from Netezza, DataStage into Azure cloud native Snowflake, MatillionDBT platform, Metadata and business glossary management, and data quality.
  • Experience in creating Data Flow Diagrams (DFD), Healthcare Payer Industry experience in designing the logical and physical data models for the Data Warehouse s per business requirements.
  • In-depth knowledge of Azure Cloud data capabilities and services, and how those relate to the development migration activities.
  • Must have hands-on experience (developmentmigration) on Azure Data Lake Gen2, Snowflake, Matillion, DBT Experience on migrating large Datahub to Cloud.
  • Experience in decommissioning coordination after migration for Source systems.
  • Good understanding of DevOps and Data pipeline automation platforms.
  • Familiarity with legal and regulatory requirements relevant to cloud data architecture, such as SOX, PCI, HIPAA, and Data Protection (GDPR, DPDP 2023).
  • Familiarity with cryptographic algorithms and security protocols. Skilled in designing and building distributed systems for processing large data volumes.
  • Excellent communication, presentation, and interpersonal skills are essential.
  • Responsibilities Lead andor assist in designing and developing cloud-based data systems, tailoring solutions to meet business requirements.
  • Develop comprehensive architecture solution migration roadmaps, seamlessly integrating business processes and technologies.
  • Design, develop, and enforce standards for data migration, storage, processing, and governance across all environments.
  • Work closely with enterprise and application architects to align the data engineering team with the overall company SDLC standards, practices, and data access patterns.
  • Develop, document, and maintain an overall view of data platform architecture, data acquisition, data quality, and data retention.
  • Provide guidance in migration of ETL jobs including developing best practices.
  • Provide formal and informal training for data engineers, platform engineers and ETL developers.
  • Maintain knowledge of emerging technologies and architectures.

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