Lead Data Architect
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Job Location:
Monthly Salary:
Posted on:
16 days ago
Vacancies:
1 Vacancy
Job Summary
The Lead Data Engineer will work very closely with the HOD and other lead architects/engineers and is responsible to push
forward the Data Management/Analytics vision and strategy to deliver common secure and consistent data capabilities
across the Group. This role will engage is strategic initiatives and reports into Head of Data Engineering
Chapter and will manage the Data architecture/engineering and design of related approaches tools and technologies.
The primary task is to drive and transform the data capabilities and enable a data-driven culture across the group and
therefore work with other architects and platform teams to ensure data is managed as an asset in a centralized
standardized and consistent manner in order to maintain consistency and quality using mature technologies and emerging
data practices.
This role requires an understanding of various data engineering and processing related technologies and choices has a
deep understanding of both SQL/No-SQL technologies distributed computing framework and techniques to make right tools
and technology choices.
3. Job Content (Describe the key results delivered by the job holder how they are measured and the tasks performed to
achieve the results)
Key Results Performance Measures Main Tasks
forward the Data Management/Analytics vision and strategy to deliver common secure and consistent data capabilities
across the Group. This role will engage is strategic initiatives and reports into Head of Data Engineering
Chapter and will manage the Data architecture/engineering and design of related approaches tools and technologies.
The primary task is to drive and transform the data capabilities and enable a data-driven culture across the group and
therefore work with other architects and platform teams to ensure data is managed as an asset in a centralized
standardized and consistent manner in order to maintain consistency and quality using mature technologies and emerging
data practices.
This role requires an understanding of various data engineering and processing related technologies and choices has a
deep understanding of both SQL/No-SQL technologies distributed computing framework and techniques to make right tools
and technology choices.
3. Job Content (Describe the key results delivered by the job holder how they are measured and the tasks performed to
achieve the results)
Key Results Performance Measures Main Tasks
1. 1. Develop and deliver long-term
strategic goals for data engineering
strategic goals for data engineering
Alignment of data and information
requirements with business
objectives and priorities
requirements with business
objectives and priorities
Develop data
architecture/engineering vision and
standards in conjunction with
business users and stewards
Outline short-term incremental
solutions to achieve long-term
objectives and an overall data
management roadmap
Create data exchange standards to
ensure reusability and a decoupled
architecture
Create standards for data archival
and purging
architecture/engineering vision and
standards in conjunction with
business users and stewards
Outline short-term incremental
solutions to achieve long-term
objectives and an overall data
management roadmap
Create data exchange standards to
ensure reusability and a decoupled
architecture
Create standards for data archival
and purging
2. Maintain an agile resilient and
secured data architecture/engineering
landscape
secured data architecture/engineering
landscape
No of critical or business disrupting
incidents
Timely and secured access to
information
Reduce data management costs
incidents
Timely and secured access to
information
Reduce data management costs
Identify and drive the
implementation of secured data
solutions
Develop data access matrix and
ensure right information reaches
the right people through secured
channels
Develop strategy to align with
external regulatory requirements
implementation of secured data
solutions
Develop data access matrix and
ensure right information reaches
the right people through secured
channels
Develop strategy to align with
external regulatory requirements
3. Establish methods and procedures
for tracking data quality completeness
redundancy compliance and
for tracking data quality completeness
redundancy compliance and
Alignment with data governance
and stewardship community
Manage and maintain enterprise
data catalogue
and stewardship community
Manage and maintain enterprise
data catalogue
Identify and document critical data
elements across source system of
records
Define and document the data
quality rules and standards
elements across source system of
records
Define and document the data
quality rules and standards
Assess and define data
governance and stewardship
maturity roadmap
governance and stewardship
maturity roadmap
4. Establish standards to document and
communicate data flow for enterprise
data warehouse and data lake
communicate data flow for enterprise
data warehouse and data lake
Document and capture the lineage
and end-to-end data flow from core
systems into enterprise data
warehouse
and end-to-end data flow from core
systems into enterprise data
warehouse
Work with data engineers and
source system experts to define
the standards and principles for
capturing lineage and data flow
Define data exception handling
processes
Define standards for data pipeline
scheduling and monitoring
source system experts to define
the standards and principles for
capturing lineage and data flow
Define data exception handling
processes
Define standards for data pipeline
scheduling and monitoring
5. Coach and mentor the data
engineering community
engineering community
Delivery of high quality and
performant data pipelines
Critical defects recorded due to
data pipeline failures and data
quality issues in production
performant data pipelines
Critical defects recorded due to
data pipeline failures and data
quality issues in production
Provide technical
recommendations and engage with
data engineers and BI leads
throughout the solutioning and
implementation lifecycle
Recommend effective solutions to
develop high performant and
scalable data pipelines
Work with source system expertise
to understand the data domains
and source to target mapping
Build and maintain canonical
datamodel to standardize data
exchange between systems and
with various architects to enforce
the same
recommendations and engage with
data engineers and BI leads
throughout the solutioning and
implementation lifecycle
Recommend effective solutions to
develop high performant and
scalable data pipelines
Work with source system expertise
to understand the data domains
and source to target mapping
Build and maintain canonical
datamodel to standardize data
exchange between systems and
with various architects to enforce
the same
4. Job Dimensions (a) List of Annual Profit/revenue/cost/volumes/portfolio etc. directly controlled or influenced by the job
holder (b) Total number of employees managed (directly and indirectly) by job holder (c) Any other key aspects relevant
to the job e.g. markets covered products managed
holder (b) Total number of employees managed (directly and indirectly) by job holder (c) Any other key aspects relevant
to the job e.g. markets covered products managed
Job Dimension Value/Description
Management of the data technology solutions their integrations and
deployment patterns as per the reference architecture More than 120 business application
Lead guide and develop the technical resources (Data Engineers)
deployment patterns as per the reference architecture More than 120 business application
Lead guide and develop the technical resources (Data Engineers)
More than 60 data engineers across both real-
time and batch
time and batch
Key Skills
- Fund Management
- Drafting
- End User Support
- Infrastructure
- Airlines
- Catia
