ScienceSoft is looking for Data Engineer.
Creating digital data platform for global manufacturer from Fortune 500 company.
Platform will be hosted in cloud and based at Microsoft Azure and aggregate data from big amount of disparate systems.
As result platform will provide Customer Data Utilization and Customer Business Intelligence for internal and external users.
Will include DataLake, DataWarehouse, Analitycal Portal, KPI Management, advanced and interactive analytics and KPI dashboards
- Selecting and implement the tools and processes required of a data processing pipeline in support of the customer requirements. Include implementing ETL pipelines, monitoring/maintaining data pipeline performance. The Data Engineer in proficient in distributed computing principles and familiar with key architectures including Lambda and Kappa architectures, and has a broad experience across a set of data stores (e.g., HDFS, Azure Data Lake Store, Azure Blob Storage, Azure SQL Data Warehouse, Apache HBase, Azure Cosmos DB), messaging systems (e.g., Apache Kafka, Azure Event Hubs, Azure IoT Hub) and data processing engines (e.g., Apache Hadoop, Apache Spark, Azure Data Lake Analytics, Apache Storm, Azure HDInsight). The ideal candidate has three or more years’ experience working on solutions that collect, process, store and analyze huge volume of data, fast moving data or data that has significant schema variability.
- Deep understanding of using data and analytics services to solve enterprise data challenges. Extensive architecture and design experience with complex applications across various data sources and platforms.
- Highly proficient in distributed computing principals and familiar with key architectures, including Lambda and Kappa architectures, and has extensive experience designing solutions leverage a diverse assortment of data sources.
- Deep understanding of common database technologies, such as SQL Database/Server, SQL Data Warehouse, Oracle, MySQL, and other data sources, such as Azure Data Lake Storage and Azure Blob Storage. Solid understanding of data governance and creating data dictionaries. Understanding of how to accelerate a customer’s digital transformation using advanced analytics, artificial intelligence (AI), and Big Data. Strong understanding of scripting languages, including R, Python and SQL.
- Proven ability to develop work in environments following agile methodologies.
- Proven track record of driving decisions collaboratively, resolving conflicts & ensuring follow through. Presentation skills with a high degree of comfort with both large and small audiences. Prior work experience in a consulting/architecture position within a software & services company. Problem solving mentality leveraging internal and/or external resources. Exceptional verbal and written communication.
- DMX, DAX, MDX, SQL, T-SQL, Python, C#, PowerShell, R
- SQL Server, SQL Server IaaS, SSIS, Azure Data Factory, Azure Data Lake, Azure Storage Azure SQL Data Warehouse, Azure HDInsight, Azure SQL Database, Power BI, Python, C#, Spark
Nice to have:
- Azure Active Directory, Azure Machine Learning, Azure Cosmos DB, Azure Analytics, APS, AWS, Amazon Athena, AWS Glue, Amazon QuickSight, AMAZON RDS, Amazon Redshift, AMAZON S3, Azure Data Catalog, Azure Stream Analytics, Azure Event Hubs, Azure IoT Hub, Azure Cognitive Services, Cassandra, Cloudera, Cortana Intelligence, Docker, Flume, Hadoop, HBase, Hive, IoT Solutions, Kafka, MongoDB, MariaDB, MySQL, Oracle, PostgreSQL, QLik Tech, Storm, Tableau, YARN.
- Opportunity for professional self-realization
- Friendly and united team
- days of paid vacation
- 100%-paid sick leave
- Language courses and other corporate programs
- Medical insurance
- Competitive (official) salary.