Key Skills
: Strong SQL, Python, Pyspark, Jupyter Notebook, Agile / Jira / Confluence,
Microsoft Excel, Banking Domain knowledge, Team Management, Pod Lead
Job Description:
Must - Have:
7+ years of professional experience as a Lead Data Analyst with good
decision-making, analytical and problem-solving skills.
SQL, Pyspark, Python with ESG / Banking Domain experience.
Hands-on experience in HQL or SQL (Spark SQL) for Data exploration.
Documentation - Data Mapping, Subsystem Design, Technical Design, Business
Requirements.
Exposure to Logical to Physical Mapping, Data Processing Flow to measure
the consistency, etc.
Understanding of ER Diagram and Data Modelling concepts.
Exposure to Data Management, Data Cleaning, Data Quality and Data
Preparation.
Exposure to working in Agile framework.
Role & Responsibilities:
Should have worked on Jira tickets creation/maintained/closed and update
the tickets with delivery updates aligned to the delivery sprint cadence.
Help to ensure L1 & L2 milestones are maintained, and statuses
reflected in dashboards and monthly reporting.
Lead a highly skilled, multi-disciplinary team of consisting of data,
analytics, technology and delivery professionals to deliver advanced data
and analytics solutions.
Act as Lead DA and Pod Lead for teams to deliver business use cases on a
global scale and deploying locally.
Coordinate the deployment of global initiatives into markets.
Working closely with data, analytics and technology teams across the
business, shape solution designs which meets business needs as well as
aligning to the broader strategic Data & Analytics objectives.
Work directly with various stakeholders across multiple geographies, such
as technical discipline leads, data scientists, data engineers and data
analysts to produce accurate delivery estimates and manage the transition
from analysis to successful delivery.
Define Agile project working approach and enforce all team members to
follow the same methodology.
Ensure awareness, involvement and support from key stakeholders by
building strong pod teams and maintaining robust communications on the
project status throughout its lifecycle.
Ensure risks and issues are identified, managed closely and remove project
blockers from the team.
Make key decisions to ensure the successful implementation of all
initiatives.
Supporting the delivery production line such as definition, implementation
and testing and ensuring deliverables meet business requirements and are
fit for purpose.
Drive all stakeholders to deliver on time and to the required quality
standards.
Ensures cross-team delivery plans exist which represent an achievable
commitment based on the capacity of available resource and consideration
of internal and external dependencies.