Role Title
BI Developer
Department
Media Business System
Location
Chennai – working for EMEA markets
About WPP IT
WPP IT provides IT services for WPP, the world’s largest communications services group. As a creative transformation company, WPP is helping its clients transform the future through extraordinary work. WPP IT is an integral part of that journey, and we are proud to provide technology for some of the world’s most creative brands.
Role purpose
At WPP, technology is at the heart of everything we do, and it is WPP IT’s mission to enable everyone to collaborate, create and thrive. WPP IT is undergoing a significant transformation to modernise ways of working, shift to cloud and micro-service-based architectures, drive automation, digitise colleague and client experiences and deliver insight from WPP’s petabytes of data.
GroupM is the world’s leading media investment company responsible for more than $63B in annual media investment through agencies Mindshare, MediaCom, Wavemaker, Essence and m/SIX, as well as the outcomes-driven programmatic audience company, Xaxis and data and technology company Choreograph. GroupM’s portfolio includes Data & Technology, Investment and Services, all united in a vision to shape the next era of media where advertising works better for people. By leveraging all the benefits of scale, the company innovates, differentiates and generates sustained value for our clients wherever they do business.
The GroupM IT team in WPP IT are the technology solutions partner for the GroupM group of agencies and are accountable for co-ordinating and assuring end-to-end change delivery, managing the GroupM IT technology life-cycle and innovation pipeline.
This role will work as part of the Local Systems Team for EMEA. You will be part of a new team BI team in Chennai, that will support our existing and future BI setup for EMEA markets. You will be responsible for delivering the solutions formulated by product owners and key stakeholders for different EMEA markets. In collaboration with the BI development team, you update the architecture and data models to new data needs and changes in source systems.
Key Responsibilities
Assist in the build, development, and management of custom databases/solutions using SSIS.
Monitoring and optimizing data processing and storage resources on GCP.
Clearly communicate technical terms to non-technical people and help them understand why change might be required to achieve a specific goal or to complete a project
Design, build and deploy ETL and data management processes. Develop and deploy ETL job workflow with reliable error/exception handling and rollback framework.
Monitoring and optimizing data processing and storage resources on GCP.
Troubleshooting and resolving data pipeline issues and performance bottlenecks.
Documenting data engineering processes, best practices, and technical specifications.
Conform to agile development practices – Evolutionary design, refactoring, continuous integration/delivery, test-driven development.
Work collaboratively with Business Partner Team and Business Stakeholder during projects scoping and feasibility phases as a SME for concept investigation/viability and technical impact; Identify and communicate technical risks and mitigations.
Provide production support for data load jobs.
Write customized query to generate automatic periodic reports.
Build applications writing SQL scripts to manipulate data and / or writing specific instructions for an off-shore programmer to write the scripts.
Maintain or upgrade existing applications.
Attend key design meetings and provide support.
Other ad hoc duties.
Skill Requirements
3+ years experience with writing TSQL (views/functions/stored procedures).
5+ years experienced engineer who has worked on environment and its relevant tools/services. (ADF, Azure Storage account, Azure SQL Server, Azure Functions, Databricks)
3+ years of strong experience in Python development (Object oriented/Functional Programming, Pandas, Pyspark etc)
Good to have DBT and DLT knowledge
Experience with major RDBMS systems like MS-SQL
Hands-on with GitHub or equivalent source control repositories
Bachelor’s degree in Computer Science, Engineering, Mathematics or other technical field is highly preferred.
Experience with data modeling, and working with star schema
Experience with the full development life cycle of an application stack - from architecture through test and deployment.
Demonstrated experience in data warehouse analysis and design, with full knowledge of data warehouse methodologies and data modelling.
Unit testing low level components – SQL scripts, Stored Procedures, ETL modules; Integration testing data transition points; Performance, load and stress testing.
Knowledge and experience in software development methodology and toolset for implementing, lifecycle and management – Agile methodology.
TFS/GIT code repository and branching strategies; Microsoft Release Management and any deployment tools; Jira knowledge.
Team player
Organized and detail oriented
Excellent communication, presentation, and writing skills
Behaviours
You’re open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.
You’re optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with confidence: to try the new and to seek the unexpected.
You’re extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we deliver extraordinary every day.
Data Engineer
Data Load Tool (DLT)PythonData BricksData Factory
Data Engineer
DBTTabular EditorData BricksDLT
BI Developer
Role Title
BI Developer
Department
Media Business System
Location
Chennai – working for EMEA markets
About WPP IT
WPP IT provides IT services for WPP, the world’s largest communications services group. As a creative transformation company, WPP is helping its clients transform the future through extraordinary work. WPP IT is an integral part of that journey, and we are proud to provide technology for some of the world’s most creative brands.
Role purpose
At WPP, technology is at the heart of everything we do, and it is WPP IT’s mission to enable everyone to collaborate, create and thrive. WPP IT is undergoing a significant transformation to modernise ways of working, shift to cloud and micro-service-based architectures, drive automation, digitise colleague and client experiences and deliver insight from WPP’s petabytes of data.
GroupM is the world’s leading media investment company responsible for more than $63B in annual media investment through agencies Mindshare, MediaCom, Wavemaker, Essence and m/SIX, as well as the outcomes-driven programmatic audience company, Xaxis and data and technology company Choreograph. GroupM’s portfolio includes Data & Technology, Investment and Services, all united in a vision to shape the next era of media where advertising works better for people. By leveraging all the benefits of scale, the company innovates, differentiates and generates sustained value for our clients wherever they do business.
The GroupM IT team in WPP IT are the technology solutions partner for the GroupM group of agencies and are accountable for co-ordinating and assuring end-to-end change delivery, managing the GroupM IT technology life-cycle and innovation pipeline.
This role will work as part of the Local Systems Team for EMEA. You will be part of a new team BI team in Chennai, that will support our existing and future BI setup for EMEA markets. You will be responsible for delivering the solutions formulated by product owners and key stakeholders for different EMEA markets. In collaboration with the BI development team, you update the architecture and data models to new data needs and changes in source systems.
Key Responsibilities
Assist in the build, development, and management of custom databases/solutions using SSIS.
Monitoring and optimizing data processing and storage resources on GCP.
Clearly communicate technical terms to non-technical people and help them understand why change might be required to achieve a specific goal or to complete a project
Design, build and deploy ETL and data management processes. Develop and deploy ETL job workflow with reliable error/exception handling and rollback framework.
Monitoring and optimizing data processing and storage resources on GCP.
Troubleshooting and resolving data pipeline issues and performance bottlenecks.
Documenting data engineering processes, best practices, and technical specifications.
Conform to agile development practices – Evolutionary design, refactoring, continuous integration/delivery, test-driven development.
Work collaboratively with Business Partner Team and Business Stakeholder during projects scoping and feasibility phases as a SME for concept investigation/viability and technical impact; Identify and communicate technical risks and mitigations.
Provide production support for data load jobs.
Write customized query to generate automatic periodic reports.
Build applications writing SQL scripts to manipulate data and / or writing specific instructions for an off-shore programmer to write the scripts.
Maintain or upgrade existing applications.
Attend key design meetings and provide support.
Other ad hoc duties.
Skill Requirements
3+ years experience with writing TSQL (views/functions/stored procedures).
5+ years experienced engineer who has worked on environment and its relevant tools/services. (ADF, Azure Storage account, Azure SQL Server, Azure Functions, Databricks)
3+ years of strong experience in Python development (Object oriented/Functional Programming, Pandas, Pyspark etc)
Good to have DBT and DLT knowledge
Experience with major RDBMS systems like MS-SQL
Hands-on with GitHub or equivalent source control repositories
Bachelor’s degree in Computer Science, Engineering, Mathematics or other technical field is highly preferred.
Experience with data modeling, and working with star schema
Experience with the full development life cycle of an application stack - from architecture through test and deployment.
Demonstrated experience in data warehouse analysis and design, with full knowledge of data warehouse methodologies and data modelling.
Unit testing low level components – SQL scripts, Stored Procedures, ETL modules; Integration testing data transition points; Performance, load and stress testing.
Knowledge and experience in software development methodology and toolset for implementing, lifecycle and management – Agile methodology.
TFS/GIT code repository and branching strategies; Microsoft Release Management and any deployment tools; Jira knowledge.
Team player
Organized and detail oriented
Excellent communication, presentation, and writing skills
Behaviours
You’re open: We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.
You’re optimistic: We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with confidence: to try the new and to seek the unexpected.
You’re extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we deliver extraordinary every day.
Data Engineer
Data Load Tool (DLT)PythonData BricksData Factory
Data Engineer
DBTTabular EditorData BricksDLT
Interview Questions (BI Developer JD)
1) SQL / T-SQL
Walk me through a complex stored procedure you wrote recently—what was the objective and how did you optimize it?
How do you troubleshoot a slow query in MS SQL Server (execution plan, stats, indexes, blocking/locks, parameter sniffing)?
CTE vs Temp table vs Table variable—when would you use each and why?
How do you design incremental loads using T-SQL (watermark/high-watermark strategy)?
How do you make ETL SQL idempotent (safe re-runs without duplicates)?
2) ETL / SSIS / Azure Data Factory (ADF)
Describe an SSIS/ADF pipeline you built end-to-end. What were the source(s), transformations, target, and schedule?
How do you implement reliable error handling, alerting, and restartability (retries, checkpoints, dead-letter/error tables)?
Explain your rollback/compensation approach when a downstream step fails after partial data loads.
How do you handle schema changes from source systems (schema drift) without breaking daily loads?
In ADF, what have you used: triggers, parameters, Key Vault, linked services, datasets, CI/CD deployments?
3) Databricks / Spark / Azure Services
ADF vs Databricks—what should run where and why? Give an example from your work.
How do you optimize Spark jobs (partitioning, shuffle, broadcast joins, caching, file formats like Parquet/Delta)?
Have you used Azure Functions in a data workflow? What problem did it solve (API calls, orchestration, notifications, custom logic)?
What is your experience with Azure Storage (ADLS/Blob): folder structure, naming conventions, access control, performance considerations?
How do you handle secrets/credentials securely in Azure (Key Vault, managed identity, service principals)?
4) Python / Pandas / PySpark
When would you use Pandas vs PySpark? What are the typical scale/performance failure points?
Show (or explain) a transformation you built using joins + window functions in PySpark.
How do you package and reuse Python code across pipelines (modules, repos, linting, unit tests, deployment)?
How do you implement and validate data quality checks in Python (null/duplicate checks, schema validation, reconciliations)?
5) Data Modelling / Star Schema / DWH
Design a star schema for a reporting use case (e.g., campaign performance). What is the grain of the fact table and what are the key dimensions?
How do you handle Slowly Changing Dimensions (SCD Type 1 vs Type 2) and where do you implement it (SQL/ETL/dbt)?
What reconciliation checks do you do to ensure warehouse numbers match source systems?
6) Testing / CI-CD / Agile
What unit tests do you write for SQL/stored procedures/ETL modules? Give examples.
How do you do integration testing at data transition points (source → staging → curated → reporting)?
Explain your branching strategy in Git/TFS and how you promote changes across DEV/UAT/PROD.
Describe a production release you supported—what was your deployment checklist and rollback plan?
7) Production Support / Monitoring
A daily load failed—how do you triage quickly (logs, data checks, rerun strategy) and communicate to stakeholders?
What monitoring/alerts have you set up for pipelines (failure alerts, SLA breaches, data quality alerts)?
How do you handle performance bottlenecks in production ETL (identify root cause, quick fix vs long-term fix)?
8) Good to have: dbt / DLT
If you’ve used dbt: how do you structure models (staging/intermediate/marts) and what tests do you typically add?
If you’ve used Delta Live Tables (DLT): what problem does it solve vs standard notebooks/jobs, and how do you manage expectations around quality/SLAs?
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