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Senior Gen AI Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 10h ago
The date the source published, not the day we noticed it (2026-10-01). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
India
The description agrees: it names India.
What the ad says
…Location: India Job…
Pay not stated
Similar roles pay $6,438–7,250/mo
Middle 50% of 8 listings that do state pay — Engineering · all levels · India · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 1h ago · last seen just now
The listing
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.
Requirements
Key Responsibilities
- Design, develop, and maintain scalable data engineering and analytics solutions.
- Build reliable and efficient data pipelines for batch and real-time data processing.
- Develop data platforms and workflows using Databricks 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 in data 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 developing scalable data pipelines and data processing solutions.
- Hands-on experience with Databricks 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 as AWS, Azure, or GCP.
- Strong programming and scripting skills in technologies such as Python, 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 emerging data, cloud, analytics, and AI technologies.