Job Description:
Job Description: Data Modeller – BI ( Project Manager)

Job Description

Unique Job Role

Data Modeller - BI

Function

Digital

Reporting to

Senior Manager - IT

Business

All

Grade

L5/L6

Date

11-Nov-2022

Job Details

Technical Lead in the Data Architecture Domain, Responsible for the design and creation of standard and benchmark data models using Layered Scalable Architecture concepts to deliver the Data Marts across all Businesses of Titan. This includes complexities like several decades of Business Data, External Data, high volume, complex structure, Performance & Costs.

Should have expertise in RDBMS concepts, data warehousing, modelling and agile concepts and have strong hands on experience in SQL

 

External Interfaces

Internal Interfaces

•         Qualitest

•         Empower sys / Aliment

•         Tableau India Pvt Ltd

•         Alpharithm

•         CRG

•         AWS

•         SAP

•         IBM

•         Google

•         Technical consultants of BI

•         Functional consultants / Business Analysts

•         Business users

•         Testing Team

•         Development Team

Job Requirements

Education

·  Scenario 1: Engineering

·  Scenario 2: MCA Graduation

Relevant Experience

·  Scenario 1: >4 Years

·  Scenario 2: >6 Years

Behavioural Skills

•         Good Communication & Interpersonal skills

•         Excellent Analytical skills- Problem solving/troubleshooting

•         Excellent Team player

Knowledge

•         Strong Technical knowledge of SQL, RDBMS, Data Warehousing and Modelling

•         Minimum 3 projects implementation experience in  Retail/Manufacturing/HR/Finance domains

•         Good Knowledge on ETL tools ( min 1 tool)

•         Good process knowledge of minimum one Domain

•         Experience in Project management – atleast 3 medium to complex project

Process Contributions

Process Contribution

Process Outcome

Performance Measure

Digital: Business KPI for Various Personas

1.      Ability to translate requirements / functional specifications to Technical Specifications and the Business KPI/ metrics based on user requirements.

2.      Calculation of various derived KPI/metrics using logic shared by business

3.      Understanding the Granularity of Data for various KPI/metrics.

 

 

 

 

·       Technical Specification

·       Metrics calculation using SQL functions / Stored Procedure

·       Dimension to Measure Matrix

 

·   Technical Specification Document of KPI/Metrics for various functions

·   Algorithm and Pseudo code to build the data mart layers

Digital: Data Requirement and  Source Mapping

1.      Data

2.      Understanding Data granularity and availability of Data in source system

·       Mapping of Data WRT source system

·       Arrive availability of Data/Granularity  for  various KPI/Metrics with source system

·       Identify Gap wrt  Data requirement.

·   Data requirement Document (DRD)

Digital: Data modelling/ LSA Build

1.      Arrive the various data elements and the logical data structure/tables

2.      Identify the relationship between various data tables structure

3.      Identify the primary key and the surrogate keys for various data structure

4.      Arrive the layers of data to be provision – source staging to final harmonisation layer/reporting layer

·   Conceptual/Logical data model

·   ER diagram

·   Data dictionary

·   Data layers and purpose

·   Build layers using SQL code with optimal performance

·   Scalable Model when new requirements or modification of KPI/data comes up

 

·   Ease of Design to accommodate changes

Digital: Testing strategy and data integrity

1.      Identify the Test criteria’s for the various data layers

2.      Arriving the test strategy along with required stake holder (Testing , ETL , Reporting team)

3.      Identify area of improvements based on the internal and user feedback

·   Testing criteria for data layers

·   Process redefine for robustness

·   Feedbacks and Data issues faced by users

Digital: Ease of Using data for Business

1.      Identify the harmonisation layers for various business

2.      Identify various mechanism for reducing the leadtimes for development of Dashboards

3.      Identify various mechanism/approaches for enabling self service

4.      Identify various mechanism for reducing the leadtimes for development of data consumptions layers ( Downstream/Ibots)

·   Datamarts

·   Data dictionary

·   Harmonisation layers

·   Lead time reduction in dashboard /consumption layer development

·   Number of users/domains on self service

                 Key Skills:
SQL, Python