Senior Gen AI Engineer

Weekday AI; India; On-site; INR 1,000,000 - 6,500,000; Full time

Job summary

Weekday AI is seeking a Data Engineering and Analytics professional in India to design, develop, and optimise modern data platforms that support analytics, BI, and AI-driven use cases. You will collaborate with engineering, analytics, product, and business teams to build robust data solutions that scale with evolving business requirements.

The role involves working with Databricks, data pipelines, data processing, analytics, and modern data architectures.

Qualifications

• 5+ years of professional experience in data engineering, analytics engineering, or a related role.
• Strong experience designing scalable data pipelines and data processing solutions.
• Hands-on experience with Databricks and modern cloud platforms.
• Knowledge of data modelling, ETL/ELT, and distributed processing.
• Experience with AWS, Azure, or GCP.
• Programming skills in Python, SQL, Scala, or Java.
• Understanding of data architecture, integration patterns, and data quality.
• Experience supporting analytics, BI, ML, or AI use cases.

Responsibilities

• Design, develop, and maintain scalable data engineering and analytics solutions.
• Build reliable data pipelines for batch and real-time processing.
• Develop data platforms and workflows using Databricks and cloud technologies.
• Work with large datasets to support analytics, reporting, and AI-driven apps.
• Design data models and optimise processing workflows for performance and scalability.
• Integrate data from multiple structured and unstructured sources.
• Implement data quality, validation, monitoring, and governance.
• Collaborate with data scientists, analysts, engineers, product teams, and stakeholders.
• Translate business requirements into scalable data solutions.
• Troubleshoot pipeline, processing, performance, and integration issues.
• Optimise existing architectures and workflows for reliability and cost.
• Contribute to cloud-based data architecture and modernisation initiatives.
• Develop reusable frameworks and best practices for data engineering.
• Support deployment, monitoring, and production maintenance of data solutions.
• Stay current with emerging data, cloud, analytics, and AI technologies.

Skills

Databricks

Data pipelines

Python

SQL

Scala

Java

Data modelling

ETL/ELT

Cloud platforms

Distributed processing

Tools

Databricks

AWS

Azure

GCP

SQL

Job description

This role is for one of the Weekday's clients

Salary range: Rs 1000000 - Rs 6500000 (ie INR 10-65 LPA)

Experience: 5+ yrs

Location: India

Job Type: Full-time

As a Data Engineering and Analytics professional, you will work on designing, developing, and optimising modern data platforms that support analytics, business intelligence, and AI-driven use cases. You will collaborate with engineering, analytics, product, and business teams to build robust data solutions that can scale with evolving business requirements.

The role involves working with cloud platforms, Databricks, data pipelines, data processing, analytics, and modern data architectures. You will contribute to end-to-end data initiatives, from understanding requirements and designing solutions to implementation, optimisation, and production support.

Key Responsibilities

• Design, develop, and maintain scalabledata engineering and analytics solutions.
• Build reliable and efficient data pipelines for batch and real-time data processing.
• Develop data platforms and workflows usingDatabricks and modern cloud technologies.
• Work with large and complex datasets to support analytics, reporting, and AI-driven applications.
• Design data models and optimise data processing workflows for performance and scalability.
• Integrate data from multiple structured and unstructured sources.
• Implement data quality, validation, monitoring, and governance practices.
• Collaborate with data scientists, analysts, engineers, product teams, and business stakeholders.
• Translate business requirements into scalable technical and data solutions.
• Troubleshoot data pipeline, processing, performance, and integration issues.
• Optimise existing data architectures and workflows to improve reliability, efficiency, and cost.
• Contribute to cloud-based data architecture and platform modernisation initiatives.
• Develop reusable frameworks, components, and best practices for data engineering.
• Support the deployment, monitoring, and maintenance of data solutions in production environments.
• Stay current with emerging technologies indata engineering, cloud, analytics, AI, and modern data platforms.

What Makes You a Great Fit

• 5+ years of professional experience in data engineering, analytics engineering, data platforms, or a related technology role.
• Strong experience designing and developingscalable data pipelines and data processing solutions.
• Hands-on experience withDatabricks and modern cloud-based data platforms.
• Strong understanding of data engineering concepts, data modelling, ETL/ELT, and distributed data processing.
• Experience working with one or more major cloud platforms such asAWS, Azure, or GCP.
• Strong programming and scripting skills in technologies such asPython, SQL, Scala, or Java.
• Experience working with relational and non-relational databases and large-scale datasets.
• Good understanding of data architecture, integration patterns, performance optimisation, and data quality.
• Experience supporting analytics, business intelligence, machine learning, or AI-driven use cases.
• Strong analytical and problem-solving skills with the ability to troubleshoot complex data challenges.
• Ability to work effectively with cross-functional and technical teams.
• Strong communication skills with the ability to explain technical concepts clearly to business stakeholders.
• Experience working in agile, fast-paced technology environments.
• Strong ownership mindset with the ability to independently drive projects from requirements through implementation and production.
• Passion for learning and experimenting with emergingdata, cloud, analytics, and AI technologies.