VP Data Engineer, GTO

You will be responsible for the end-to-end softwaredevelopment and support for all work related to Enterprise Data Warehouse (EDW)projects, quarterly change requests, L3 production fixes. This includessoftware product implementation and administration, application design,development, implementation, testing and support. You will be expected to workon Data team.

You will also be responsible for quality assurance of the team’s delivery inconformance with the Bank-defined software delivery methodology and tools. Youwill partner with other technology functions to help deliver requiredtechnology solutions.

• Create frameworks, technical features which helps in faster operationalisation of Data models, Analytical models(including AI/ML) and user generated contents (dashboards, reports etc)
• Effectively partner with citizen data scientists in enabling faster adoption of AL/ML model based systems
• Independently install, customise and integrate software packages and programs
• Carry out POCs involving new data technologies
• Design and develop application frameworks for data integration
• Create technical documents such as solution design, program specifications for target solutions
• Perform design and development of applications which may not be limited to: Software Applications, Data Integration, User Interfaces, Automation Maintain and recommend software improvements to ensure a platform centric management of software applications
• Performance tuning
• Work with production support team members to conduct root cause analysis of issues, review new and existing code and/or perform unit testing
• Perform tasks as part of a cross functional development team using agile or other methodologies and utilising project management software

• Hands-on experience in implementing large scale data warehouse, Data mart & analytics platforms in financial services industry with good functional knowledge of products & services offered in Retail bank / Wholesale / Global Markets covering some of the following analytics domains:
• Experience in Data Modeling, Data mapping for Data Warehouse and Data Marts solutions
• Expertise in FSLM or similar industry models
• Expertise in Reference data management – Tools experience such as MDM (Master Data Management)
• Experience in functional domain - Retail , Wholesale, Compliance , Digital
• Experience in analytics - Retail Analytics
• Expertise in design of role based fine grained access control
• Designing cloud ready data solutions, Virtualization  

• Technical skillsets -ML Model operationalization, Building Data Pipelines and Hadoop based Data marts
• Expertise in implementing Big Data frameworks using multiple SQL engine such as Spark, Impala, Hive, etc
• Expertise in implementing Hadoop based Data mart using Spark based framework (Java, Scala, Pyspark)
• Leverage LLM model to build intelligent data applications (eg: Natural Language based SQL generation)
• Experience in end to end AI / ML life cycle (Data pipeline, model training, Model development, deployment, fine tuning, etc)
• Expertise in building Data federation solution(Trino, Presto, Dremio, Query Grid) along with Data caching / Indexing
• Experience in working with any of Data Catalog tools and Automating Data Quality checks using frameworks
• Good Working experience in core technical area using Python, Java, PySpark and Scala
• Expertise in Cloudera CDP components
• Good knowledge in developing Spark based ingestion framework (Java, Scala, Pyspark)
• Experience in building and operationalising feature pipeline to support AI/ML model execution, data pipelines for supporting large scale data warehouse/data marts

• Additional requirements - 2 to 3 technical certifications from enclosed list:
• Cloudera Hadoop distribution–Hive, Impala, Spark, Kudo, Kafka, Flume
• Teradata–Bteq, Query Grid, GCFR, MDM, TAS, Data Mover, BAR
• Informatica Data Integration – PC, IDR, BDM, MM, IDQ, EDC
• Data modelling tools (Erwin)
• QlikSense
• Microsoft – R
• Data science workbenches – Cloudera Machine Language, Jupyter, DataRobot, H2O.AI, IBM DSX
• Data Virtualization tool (Denodo, Dremio)
• AS400
• Language – SQL, Java, Python, Scala, Pyspark
• Automation / scripting – CtrlM, Shell Scripting, Groovy