Design, develop, and optimize scalable data platforms, pipelines, and processing workflows using Databricks and cloud technologies. Integrate structured and unstructured data, develop models, implement quality and governance practices, and support analytics, business intelligence, machine learning, and AI use cases. Collaborate with cross-functional teams to translate requirements into technical solutions, troubleshoot production issues, modernize architectures, and improve reliability, performance, and cost.
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.
RequirementsKey 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.
- 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.
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