Data Engineer

3–5 Years
. Strong hands on experience in data engineering and ETL/ELT development. . Good experience with Snowflake, Databricks and/or AWS data services. . Strong SQL and data transformation skills. . Exposure to cloud based data platforms and data pipelines. Role Overview We are looking for experienced Data Engineers with strong hands on experience in designing, developing and enhancing modern data engineering solutions. The role will involve working with cloud data platforms, data pipelines, data integration, data transformation and analytics solutions. The ideal candidate will have strong experience in Snowflake, Databricks and AWS data services, along with good SQL and data engineering fundamentals. The role will primarily focus on development and enhancement activities, with some involvement in deployment, monitoring and production support as part of the overall application lifecycle. Key Responsibilities . Design, develop and maintain scalable data pipelines and data engineering solutions. . Develop data ingestion, transformation and processing workflows using cloud based technologies. . Work with Snowflake and Databricks to build and optimize data processing and analytical solutions. . Develop and maintain data pipelines using AWS Glue, S3 and Lambda. . Implement data transformation, cleansing, validation and integration processes. . Develop efficient SQL queries and optimize data processing and warehouse workloads. . Work with business and technical teams to understand data requirements and translate them into technical solutions. . Participate in solution design, development, testing and deployment activities. . Develop reusable components and follow established data engineering and coding standards. . Troubleshoot data pipeline and application issues and implement appropriate fixes. . Participate in code reviews, technical discussions and continuous improvement initiatives. . Support deployment and release activities across environments. . Monitor data pipelines and proactively identify issues affecting data processing or availability. . Provide support for production issues when required, including troubleshooting and root cause analysis. . Maintain technical documentation and operational procedures. Required Technical Skills Data Engineering . Strong understanding of data engineering concepts, ETL/ELT and data pipelines. . Hands on experience with Snowflake and/or Databricks. . Experience building data pipelines and data transformation workflows. . Strong SQL skills. . Good understanding of data modelling and data warehousing concepts. AWS Hands on experience with one or more of the following: . AWS Glue . Amazon S3 . AWS Lambda Experience with additional AWS data services will be an advantage. Databricks . Databricks data engineering . Data transformation and processing . Delta Lake . PySpark and/or Spark . Notebook based development Snowflake . Snowflake development . Data loading and transformation . SQL development . Data warehouse concepts . Performance optimization Preferred / Optional Skills The following skills are not mandatory, but candidates with experience in these areas will be preferred: . ODI (Oracle Data Integrator) . OAC (Oracle Analytics Cloud) . PL/SQL . Amazon MSK / Kafka . Datadog . Python . PySpark . CI/CD and DevOps practices . Git . Cloud monitoring and logging . Experience with Oracle databases Education Bachelor's degree in Computer Science, Information Technology, Engineering or a related discipline. Key Competencies . Strong data engineering and analytical skills . Good understanding of cloud data platforms . Strong SQL and data transformation capabilities . Problem solving and troubleshooting skills . Good communication and collaboration skills . Ability to work independently as well as part of a team . Strong focus on data quality and solution reliability . Ability to learn and work across new technologies and platforms

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