Must Have
- Should have minimum of 15 Years of exp and familiar with analytics skills on data lake environment for Risk and Regulatory reporting with SLA commitment
- Should have strong business knowledge on Risk and Regulatory data for understanding business terms and analyse required data independently in Data lake environment using various tools to query/check data
- Should have hands on experience in Sql Databases, ETL tools. Preparing data using Pyspark, Dataframes, bteq for analysis
- Strong in Data Operating Models for implementation of Transformations, Data Lineage, Metadata Management, Data Quality and profiling of Critical data under Consent Order programs for Banking Risk portfolios
- Should have basic understanding on Erwin, Collibra, Hadoop, R, Python and Py spark for Data governance.
- Should have knowledge to understand SAS programming, big data eco system
Good to have
- Having development knowledge on ETL tools like Datastage, Talend, Teradata Bteq
- Having more consumer banking domain knowledge
- Having be familiarity with reporting tool such as SAS, Tableau, Micro Strategy, Cognos, Power-BI for cresting the marts.
Roles & Responsibilities
- Should have extensive experience of Multi-country roll out of data transformation programs
- To understand the business requirements from various LOBs and convert into scoped functional requirements for Risk and Regulatory reporting projects/programs and delivery in Dake lake environment
- To work for solutioning of the requirement with various business stakeholders and cross functionals teams and prepare design documentation, BRD, FRD and data mappings
- To handle Data Lineage, Modelling, Meta Data Management and profiling for critical Data Elements
- To decode business logic from legacy / SAS applications used by business and convert into ETL logic for Big data, Pyspark or Ingestion tools like Datastage
- To analysis data from various databases like Teradata, Hive, Hbase, SAS & Oracle
- To plan for project delivery in agile methodology
- To manage Developers to make them understand the requirements and deliver in committed sprints
- To handle the stakeholder and business reporting for project status and risks
- To handle PAT validations with data quality checks and KPIs reporting
