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Sr. Data ETL Architect
1 month ago
1+ Years
Mandatory Skills
- Data Analytics
- Data Architecture
- Healthcare Domain exp.
- Microsoft PowerBI
- AWS/Azure/GCP Cloud
- datastage, netezzza, snowflake or Matillion
Job Description
10+ years of experience with expertise around Data architecture for medium to complex Data Analytics projects.
Must have healthcare domain experience.
Must have experience on dataStage, Netezzza, Snowflake or Matillion
Architecture & Design, Metadata and business glossary management, and data quality.
Experience in creating Data Flow Diagrams (DFD)
Experience in designing the logical and physical data models for the Datawarehouse as per business requirements
In-depth knowledge of Azure/AWS/GCP Cloud capabilities and services and how those relate to the development activities.
Handson experience with Snowflake, Mattilion, DataStage
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 and/or assist in designing and developing cloud-based data systems, tailoring solutions to meet business requirements.
Develop comprehensive architecture solution roadmaps seamlessly integrating business processes and technologies.
Design, develop and enforce standards for data storage, processing, and governance across all environments.
Work closely with enterprise and application architects to align the data engineering team to the overall company SDLC standards, practices, and data access patterns.
Develop, document, and maintain overall view of data platform architecture, data acquisition, data quality, and data retention.
Provide guidance in administration 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