Senior Gen AI Engineer (Freelancer)
Quick Summary
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ญ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฒ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ญ๐ฌ-๐ฒ๐ฑ ๐๐ฃ๐)
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
~1 min readResponsibilities
~1 min read- โDesign, develop, and maintain scalable data engineering and analytics solutions.
- โBuild reliable and efficient data pipelines for batch and real-time data processing.
- โDevelop data platforms and workflows using Databricks and modern cloud technologies.
- โWork with large and complex datasets to support analytics, reporting, and AI-driven applications.
- โDesign data models and optimise data processing workflows for performance and scalability.
- โIntegrate data from multiple structured and unstructured sources.
- โImplement data quality, validation, monitoring, and governance practices.
- โCollaborate with data scientists, analysts, engineers, product teams, and business stakeholders.
- โTranslate business requirements into scalable technical and data solutions.
- โTroubleshoot data pipeline, processing, performance, and integration issues.
- โOptimise existing data architectures and workflows to improve reliability, efficiency, and cost.
- โContribute to cloud-based data architecture and platform modernisation initiatives.
- โDevelop reusable frameworks, components, and best practices for data engineering.
- โSupport the deployment, monitoring, and maintenance of data solutions in production environments.
- โStay current with emerging technologies in data engineering, cloud, analytics, AI, and modern data platforms.
- 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.
Location & Eligibility
Listing Details
- Posted
- August 31, 2026
- First seen
- September 29, 2026
- Last seen
- September 29, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 16%
- Scored at
- September 29, 2026
Signal breakdown
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