Data Engineer with Azure

IBM Client Innovation Center Central & Eastern Europe (CEE) was established in 2012 by joining several centers in Europe. The Delivery Center is part of a global network of 80 similar centers and uses the best IBM methods of work, global processes and techniques. The center has achieved CMMI Level 5 (Capability Maturity Model Integration) and its mission is to provide customers with software solution customized to their global business needs.

Relevant experience delivering Development projects, involvement in all the phases of the software development life cycle
Relevant experience in building complex data pipelines using any industry-standard ETL tools such as SSIS, Informatica, DataStage, Oracle Data Integrator, Ab Initiom etc
Data modelling (conceptual, logical)
Performance optimization techniques
Dimensional modeling techniques –dimensions, facts, surrogate key generation, data harmonization, etc.

Preferred Professional and Technical Expertise :
Azure Cloud experience in any of the following architecture components:

Data Storage (File storage: Azure Storage blobs, Azure Data Lake Store, NoSQL databases: Azure Cosmos DB, HBase on HDInsight, SQL databases: SQL Server, Synapse Analytics)
Batch processing ( Azure Synapse Analytics, Azure Databricks, HDInsight
Stream processing (Azure Stream Analytics, HDInsight with Spark Streaming, Apache Spark in Azure Databricks, Azure Functions, Azure App Service WebJobs)
Real-time message ingestion (Azure Event Hubs, Azure IoT Hub, Kafka on HDInsight)
Analytical data store(Azure Synapse Analytics, Azure Synapse Spark pools, Azure Databricks, Azure SQL Database)
Analysis and reporting (Power BI, Jupyter Notebooks, Microsoft Azure Notebooks)
Orchestration (Azure Data Factory, Azure Logic App, Apache Oozie)

As a successful Data Engineer, you will be involved in the design, development and maintenance of big data and analytics solutions.
You will implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies, fulfilling the following responsibilities:

Align architecture solution with business requirements
Research new industry and business trends to address new demand in the emerging and dynamic domain of Big Data
Use large data sets to address business issues
Identify ways to improve data reliability, efficiency and quality
Data preparation, predictive and prescriptive data modeling
Deploy analytics programs, machine learning and statistical methods using specific programming language and tools
Deliver relevant insights and updates to stakeholders based on analytics results

If you thrive in a dynamic, collaborative workplace, IBM provides an environment where you will be challenged and inspired every single day. And if you relish the freedom to bring creative, thoughtful solutions to the table, there’s no limit to what you can accomplish here.