Data Engineer & Business Intelligence Analyst

Model Business Services; SECTOR 78; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Model Business Services is seeking a Data Engineer in India to design, develop and maintain scalable data platforms for BI, reporting and advanced analytics. You will build ingestion pipelines from Salesforce and other systems, create Bronze/Silver/Gold data layers, and ensure data quality and governance across pipelines.

The role requires strong SQL, PySpark, API integration and experience with cloud platforms (Azure/Snowflake/Databricks).

Qualifications

• Experience developing and maintaining data pipelines using ETL/ELT principles.
• Strong SQL skills and experience using PySpark for data transformation and processing.
• Experience working with APIs and integrating data from third-party SaaS platforms.
• Experience building analytical data models and data transformations.
• Experience working with cloud-based analytics platforms such as Microsoft Fabric, Azure Data Factory, Snowflake, Databricks or similar technologies.
• Experience designing and implementing Data Warehouse, Lakehouse and Medallion Architecture solutions.
• Strong understanding of data quality, validation and governance principles.
• Experience using Git or similar source control systems.
• Experience developing Power BI semantic models and dashboards.
• Strong analytical and problem-solving skills with excellent attention to detail.

Responsibilities

• Design, develop and maintain scalable data ingestion pipelines from internal and third-party systems (e.g. Salesforce, marketing platforms, finance systems, HR systems and operational applications).
• Build, maintain and optimise Bronze, Silver and Gold data layers within the organisation's analytics platform.
• Develop ETL/ELT processes to cleanse, transform and standardise data from multiple sources.
• Design and maintain Lakehouses and analytical data structures to support analytics and AI use cases.
• Monitor and maintain data pipelines, proactively identifying and resolving data quality, performance and reliability issues.
• Implement data validation, monitoring, auditing and lineage processes to ensure high levels of data integrity and governance
• Work closely with Product, Engineering, Finance, Marketing and other business functions to onboard new data sources and deliver data solutions.

Skills

ETL/ELT development

SQL

PySpark

Data governance

Git

Education

Degree in Computer Science, Data Engineering, Information Systems, Mathematics or related

Tools

Power BI

Azure Data Factory

Snowflake

Databricks

Microsoft Fabric

Job description

We are seeking a skilled and detail-oriented Data Engineer to design, develop, and maintain scalable data platforms that enable business intelligence, reporting, and advanced analytics. The ideal candidate will have strong expertise in ETL/ELT development, cloud-based data platforms, SQL, PySpark, and Power BI. This role requires close collaboration with cross-functional teams to build reliable, high-quality data solutions that support strategic decision-making.

Role & responsibilities

Data Engineering & Platform Development

• Design, develop and maintain scalable data ingestion pipelines from internal and third-party systems (e.g. Salesforce, marketing platforms, finance systems, HR systems and operational applications).
• Build, maintain and optimise Bronze, Silver and Gold data layers within the organisation's analytics platform.
• Develop ETL/ELT processes to cleanse, transform and standardise data from multiple sources.
• Design and maintain Lakehouses and analytical data structures to support analytics and AI use cases.
• Monitor and maintain data pipelines, proactively identifying and resolving data quality, performance and reliability issues.
• Implement data validation, monitoring, auditing and lineage processes to ensure high levels of data integrity and governance
• Work closely with Product, Engineering, Finance, Marketing and other business functions to onboard new data sources and deliver data solutions.

Business Intelligence & Analytics

• Design, build and maintain semantic models, Power BI semantic models and dashboards that provide accurate and timely insights to stakeholders.
• Develop reusable KPI calculations, business logic and data models to ensure consistency across BI solutions.
• Support the production of board, executive and operational BI where required.
• Partner with stakeholders to understand BI and analytical requirements and translate these into scalable data solutions.
• Identify opportunities to improve BI processes, automate manual activities and enhance access to business information

Preferred candidate profile

Qualifications

• Degree in Computer Science, Data Engineering, Information Systems, Mathematics or a related discipline preferred but not essential

Essential

• Experience developing and maintaining data pipelines using ETL/ELT principles.
• Strong SQL skills and experience using PySpark for data transformation and processing.
• Experience working with APIs and integrating data from third-party SaaS platforms.
• Experience building analytical data models and data transformations.
• Experience working with cloud-based analytics platforms such as Microsoft Fabric, Azure Data Factory, Snowflake, Databricks or similar technologies.
• Experience designing and implementing Data Warehouse, Lakehouse and Medallion Architecture solutions.
• Strong understanding of data quality, validation and governance principles.
• Experience using Git or similar source control systems.
• Experience developing Power BI semantic models and dashboards.
• Strong analytical and problem-solving skills with excellent attention to detail.

Desirable

• Experience implementing CI/CD practices for analytics solutions.
• Experience working with large-scale BI or analytics platforms.

Personal Skills

• Strong technical curiosity and passion for building scalable data solutions.
• Ability to work independently and take ownership of technical delivery.
• Excellent problem-solving and troubleshooting skills.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Ability to manage multiple priorities in a fast-paced environment.
• Strong attention to detail and commitment to data quality.
• Collaborative approach with the ability to work effectively across business and technical teams.
• Continuous improvement mindset with a desire to identify and implement better ways of working.