Big Data Support Engineer

POSITION GENERAL DUTIES AND TASKS:
Skillset
- Up to 9 years of IT experience & 5+ Years on Hadoop and K8s Eco Systems
- Last 3 years of relevant experience in banking/financial services industry
- Demonstrable analytical skills with deep knowledge of Big Data Ecosystem in a Production Support Environment.
- Hands On Experience within the Hadoop Tool Sets Hive, Hue, Spark, Kafka, Kudu, Flink, Ozone, Kafka and Streaming.
- Strong SQL, Python, Java and Unix shell scripting
- Incident, problem, and service Outage management experience is Plus.
- Good Communication and Articulation Skills

Roles/Responsibilities
- Strong in data engineering concepts and programming
- Experience in building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Experience in supporting data transformation, data structures, metadata, dependency and workload management.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Provide operational support and ensure SLI of Applications
- Troubleshoot Batch Issues & root causes to Mitigate Impacts to SLA
- Proactively Identify and Identify opportunities for preventive Maintenance
- Perform Administration & Optimization to achieve of Optimal System Performance
- Conduct review of technical and functional solutions from enhancement/project team to ensure they conform to Established Standards
- Recommend Design and Operational Optimizations
- Respond on time to the queries raised by various business units
- Provide Timely updates (Status, Progress, Issues, Resolutions) to Business Stakeholders
- Work with Project/Enhancement Teams to Review, Transition for Run Team
- Participate in Disaster Recovery and Business Continuity exercises
- Support relevant software/platform/database upgrade for the systems

Datawarehouse Support Engineer (EDW)

The support specialist will be a techno functional support team member for the Enterprise Datawarehouse (EDW) under IT BAU team.

He/she is responsible for ensuring system availability and timely deliverables for datamarts for various business unit like Finance, regulatory, Campaign.

Roles/Responsibilities
- Responsible to provide BAU support for Enterprise Datawarehouse
- Responsible to provide operational support and ensure SLI of system availability, batch deliverables
- Respond on time to the queries raised by various business units
- Provide timely updates regarding production status and progress of issue resolution
- Conduct review of technical and functional solutions from enhancement/project team to ensure they conform to IT standards
- Perform impact analysis of enhancements/projects that will impact supported systems
- Identify the underlying problems, analyse the root causes, provide possible solutions/fixes, and respond to users within SLA
- Support relevant software/platform/database upgrade for the systems
- Work with delivery team for smooth transition from projects/enhancements to BAU Mode
- Incident, problem, and service outage management experience
- Participate in Disaster Recovery and Business Continuity exercises
- Able to support relevant software/platform/database upgrade for the systems
- Server Performance, capacity, utilization monitoring and Health monitoring
- Collaborate with diverse cross functional teams within IT and Business to Independently drive outcomes
- At least 3+ years of relevant experience in banking/financial services industry
- Experience with Teradata FSLDM and data mapping
- Hands-on technologist, strong in SQL, UNIX and Teradata tools and technologies
- Experience in designing high throughput fault tolerant data pipelines for Batch (ETL/ELT)
- Experience in GL Data reconciliation between systems, datamarts & report and Knowledge of the ledger balance reporting is an added advantage
- Experience in Performance Tuning on Teradata or other MPP data pipeline
- Hands On Experience within the Hadoop Tool Sets Hive, Hue, Spark, Kafka is a plus