Working knowledge / experience of Big Data frameworks like
Hadoop, Hive and Spark.
Hands-on experience in query languages like
HQL or SQL (Spark SQL)
for Data exploration.
Data mapping: Determine the data mapping required to join multiple data sets
together across multiple sources.
Documentation -
Data Mapping, Subsystem Design, Technical Design, Business Requirements.
Exposure to Logical to Physical Mapping, Data Processing Flow to measure the
consistency, etc.
Data Asset design / build: Working with the data model / asset generation
team to identify critical data elements and determine the mapping for
reusable data assets.
Understanding of
ER Diagram
and
Data Modelling concepts
Exposure to
Data quality validation
Exposure to
Data Management, Data Cleaning and Data Preparation
Exposure to
Data Schema analysis.
Exposure to working in
Agile framework.
Knowledge of
Credit Risk Frameworks
such as
Basel II, III, IFRS 9
and
Stress Testing
and understanding their drivers - advantageous
Responsibilities
Ability to convert business problem to an analytical problem and then
finding pertinent solutions
Overall business understanding of BFSI domain
Providing high-quality analysis and recommendations to business problems.
Efficient project management and delivery
Ability to conceptualize data driven solutions for the business problem at
hand for multiple businesses/region to facilitate efficient decision making
Focus on driving efficiency gains and enhancement of processes.
Use of data to improve customer outcomes through the provision of insight
and challenge
Understand the business requirements from the product/project stakeholders
and break the requirements into simpler stories and tasks and do the
necessary mapping of the tasks to the logical model of the solutions.
Mapping of business entities to technical attributes with the logic for
transformation defined clearly.
Be accountable for the delivery of the tasks in the defined timelines with
good quality.
Working with the team leads closely and contribute to the smooth delivery of
the project.
Understand/define the architecture and discuss the pros-cons of the same
with the team.
Involve in the brainstorming sessions and suggest improvements in the
architecture/design.
Working with other teams leads to getting the architecture/design reviewed.
Keep all the stakeholders updated about the project, task status, risks, and
issues if any.
Qualifications
Graduate in Computer Science, Data Science, or related field. 2 - 3 years of
experience in data engineering or related field.