Description Design, develop, and maintain scalable and robust data solutions in the cloud using Apache Spark and Databricks. Gather and analyse data requirements from business stakeholders and identify opportunities for data-driven insights. Build and optimize data pipelines for data ingestion, processing, and integration using Spark and Databricks. Ensure data quality, integrity, and security throughout all stages of the data lifecycle. Collaborate with cross-functional teams to design and implement data models, schemas, and storage solutions. Optimize data processing and analytics performance by tuning Spark jobs and leveraging Databricks features. Provide technical guidance and expertise to junior data engineers and developers. Stay up to date with emerging trends and technologies in cloud computing, big data, and data engineering. Contribute to the continuous improvement of data engineering processes, tools, and best practices. Benefits Bachelor’s or master’s degree in computer science, engineering, or a related field. 10+ years of experience as a Data Engineer, Software Engineer, or similar role, with a focus on building cloud-based data solutions. Strong experience with cloud platforms such as Azure or AWS. Proficiency in Apache Spark and Databricks for large-scale data processing and analytics. Experience in designing and implementing data processing pipelines using Spark and Databricks. Strong knowledge of SQL and experience with relational and NoSQL databases. Experience with data integration and ETL processes using tools like Apache Airflow or cloud-native orchestration services. Good understanding of data modelling and schema design principles. Experience with data governance and compliance frameworks. Excellent problem-solving and troubleshooting skills. Strong communication and collaboration skills to work effectively in a cross-functional team.

Description Develop, maintain, and optimize backend services using Node.js and JavaScript. Architect and deploy applications using AWS Lambda and Serverless Framework. Ensure efficient integration of AWS services such as Cognito, DynamoDB, RDS, ECS, ECR, EC2, IAM. Implement and manage containerized environments using Docker. Collaborate with cross-functional teams to ensure seamless application performance. Design and optimize database interactions, ensuring high availability and performance. Troubleshoot and resolve technical issues related to backend services. Implement best security practices for cloud-based applications. Requirements Strong expertise in Node.js & JavaScript. Deep understanding of AWS Lambda and Serverless Framework. Hands-on experience with Docker and container orchestration tools. Proven ability to work with AWS services (Cognito, DynamoDB, RDS, ECS, ECR, EC2, IAM). Strong knowledge of RESTful APIs and microservices architecture. Hands on in writing SQL Experience with CI/CD pipelines for efficient deployment. Ability to optimize backend performance and scalability. Solid understanding of security and compliance in cloud environments.

Description Experience Required: 4 to 6Years Mandate Mode of work: Remote Skills Required: Azure Data Factory, SQL, Databricks, Python/Scala Notice Period : Immediate Joiners/ Permanent(Can join within July 4th 2025 ) Design, develop, and implement scalable and reliable data solutions on the Azure platform. Collaborate with cross-functional teams to gather and analyze data requirements. Design and implement data ingestion pipelines to collect data from various sources, ensuring data integrity and reliability. Perform data integration and transformation activities, ensuring data quality and consistency. Implement data storage and retrieval mechanisms, utilizing Azure services such as Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Monitor data pipelines and troubleshoot issues to ensure smooth data flow and availability. Implement data quality measures and data governance practices to ensure data accuracy, consistency, and privacy. Collaborate with data scientists and analysts to support their data needs and enable data-driven insights. Requirements Bachelor’s degree in computer science, Engineering, or a related field. 4+ years of experience with Big Data technologies like Azure Strong knowledge and experience with Azure cloud platform, Azure Data Factory, SQL, Databricks, Python/Scala. Experience in SQL and experience with SQL-based database systems. Hands-on experience with Azure data services, such as Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Experience with data integration and ETL (Extract, Transform, Load) processes. Strong analytical and problem-solving skills. Good understanding of data engineering principles and best practices. Experience with programming languages such as Python or Scala. Relevant certifications in Azure data services or data engineering are a plus.