Azure Data Engineering-Technical Lead
4 weeks ago
Experience Requirements
- Overall 8-10 years of IT experience preferably in Data and Analytics implementation.
- 4-5 years of Data engineering (Both On-prem and Azure) delivery experience including Architecture / analysis / development / configuration/ deployment.
- 4 years of implementation experience in Azure Data engineering projects
- Mandatory to have knowledge of Big Data Architecture Patterns and experience in the delivery of end-to-end Big Data solutions on Azure Cloud.
- Expert in Python/SQL/SparkSQL/PySpark
- Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, Datra bricks, perview and Azure App Service is required.
- Extensive hands-on experience implementing data migration and data processing using Azure services: Serverless Architecture, Azure Storage, Azure SQL DB/DW, Data Factory, Azure Stream Analytics, Azure Analysis Service, Databricks Azure Data Catalog, Cosmos Db, Azure Functions, ARM Templates, Azure DevOps, CI/CD etc.
- Expert in at least one distributed data processing framework: Spark (Core, Streaming, SQL), Storm or Flink, etc.
- Expert in distributed messaging and ingestion frameworks (Kafka, Pulsar, Pub/Sub, etc) and good to know traditional ETL tools like Informatica, SSIS, etc
- Should have worked on any NoSQL solutions like Mongo DB, Cassandra, HBase, Cosmos DB etc, or Cloud-based NoSQL offerings like DynamoDB, Big Table, etc.
- Good Exposure in development with CI / CD pipelines. Knowledge of containerization, orchestration, and Kubernetes engine would be an added advantage.
- Designing and building of data pipelines using API ingestion and Streaming ingestion methods.
- Knowledge in Azure Databricks, Azure IoT, Azure HDInsight + Spark, Azure Stream Analytics, Power BI is desirable.
- Strong problem solving and troubleshooting skills.
- Experience in working in a fast-paced agile environment.
- Strong experience in common data warehouse modelling principles including Kimball, Inmon.
- Experience with data visualization tools such as Power BI.
- Experience in Streaming and batch architecture (e.g., Kafka, Kafka streams, Spark, Flink)
Knowledge Requirements
- Excellent understanding of data technologies landscape/ecosystem (Both On-prem and Cloud)
- Detailed knowledge of Software development essential.
- Detailed knowledge of SQL (Structured Query Language) programming is essential.
- Proven experience in business and technical problem-solving skills is essential.
- Proven ability to build, manage and foster a team-oriented environment
- Proven ability to work creatively and analytically in a problem-solving environment
- Excellent communication (written and oral) and interpersonal skills
- Excellent organizational, multi-tasking, and time-management skills
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