Website:
mycareernet.co
Job details:
Key Skills: ETL, Abinitio, Metadata, Data
Roles and Responsibilities:
- Demonstrate understanding of how different Abinitio products communicate with each other in on-prem deployments
- Demonstrate understanding of how different Abinitio products communicate with each other in K8 (Kubernetes) deployments
- Design, develop, and enhance the Data Fabric Framework's existing capabilities
- Build generic solutions for complex data ingestion scenarios using ETL workflows and Abinitio batch/continuous graph concepts
- Develop and maintain Abinitio data ingestion frameworks and ingestion components
- Create custom extractors and support Metadata hub UI customization and extension sets
- Implement and maintain automated testing using Abinitio, including writing regression test packs
- Work on webservice components in Abinitio and support integration needs across services
- Apply strong knowledge of Metadata Hub and related discovery/catalog/query components, including modifying the Metadata Hub Meta Model
- Run and support Abinitio pipelines in GKE (Kubernetes environments) and ensure smooth execution in containerized setups
- Exhibit excellent problem-solving skills, attention to detail, and the ability to handle complex troubleshooting across ingestion and metadata layers
Skills Required:
- Strong experience in Ab-Initio development and administration
- Hands-on experience in ETL design and development
- Strong understanding of Data Ingestion frameworks and pipelines
- Expertise in Ab-Initio GDE (Graphical Development Environment)
- Knowledge of Metadata Hub and metadata management concepts
- Experience in building and maintaining data ingestion components and frameworks
- Understanding of batch and continuous graph processing in Ab-Initio
- Experience with custom extractors and data processing workflows
- Knowledge of web services integration in Ab-Initio
- Experience in test automation and regression testing using Ab-Initio
- Ability to troubleshoot and resolve complex ETL and pipeline issues
- Understanding of on-prem and Kubernetes (GKE) based deployments
- Familiarity with containerized environments and pipeline execution in K8s
- Strong problem-solving and analytical skills
- Attention to detail in handling large-scale data systems
- Good understanding of data architecture and data engineering concepts
- Strong communication and collaboration skills for working with cross-functional teams
Education : Relevant degree in Computer Science/Engineering or equivalent practical experience (degree details not specified).
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