A successful resource would be someone with 7+ years of experience in a fast-paced business-focused environment, an expert data modeler with extensive experience in building end to end Data pipelines on Azure from any given data source which would include Structured/Unstructured, AVRO, Parquet, CSV, other file systems, Streaming, Messaging, and application data sources.
Should have extensive experience in overall architecture and utilization of Azure Data Factory, Azure Synapse Analytics, Azure SQL/DW, Azure Analysis Services
Ability to ensure on-time project delivery to the client worked in an Agile application lifecycle management framework, strong communicator, and ability to question the status quo
Responsibilities
As part of our Miracle Soft Data Practice and Analytics group, the Data Engineer will participate in the design, development, and maintenance of end-to-end Business Intelligence solutions with Microsoft’s BI Stack (Power BI, SSIS, SSRS, SSAS, ADF, Azure Analysis Services, Azure Synapse Analytics, etc)
The role will involve working with technical and business teams to understand KPIs and Metrics towards building the semantic layer and ensuring that the data is available within the DW
The Azure Data Engineer will prioritize work in alignment with business objectives and strategies and think like an entrepreneur when addressing various client challenges
Qualifications
7+ years experience working in a data function where the primary responsibility is working with data, database design, data development, and ETL is the primary responsibility
Help developers understand the business requirement and develop detail technical solution specifications while working with Business, Solution, Technical, and Data Architectures teams
Participate in the analysis, design, and development of systems, including logical and physical data modeling, database design, database creation, and evaluation of data and information requirements for new applications and reports
Conduct technical discovery, identifying pain points, business, and technical requirements
2-3 years of experience working on Data bricks, Azure Data Factory, Azure Synapse Analytics, and other Azure data solutions ecosystems (Mandatory)
2 years of development experience in Snowflake, Azure SQL DW, or Big Query
2-3 years of experience working on Spark SQL, Hive SQL, U-SQL, Scala, and Python
2-3 Experience in creating the frameworks towards building the data pipelines (Mandatory)
Experience in configuring the data streams between Event Hub and Azure Service Bus with other integrated systems such as Data Bricks etc
Well versed in DevSecOps and CI/CD deployments
Cloud migration methodologies and processes including tools like Azure Data Factory, Data Migration Service, SSIS, Attunity (Qlik), Event Hub, Kafka, etc
Experience in data mining techniques and methodologies (data prep/modeling, classification, regression, clustering, causal modeling, AI, machine learning, ensemble approaches)
Advanced experience in data visualization tools with a strong grasp of effective data modeling and visualization practices
Design and Develop Business Intelligence solutions with combining knowledge of SSIS/SSAS/SSRS/Azure Analysis Services/Azure Data Factory/Power BI technologies
Perform advanced data analytics by designing and building solutions using technologies such as Azure Data Factory, Azure Data Lake, HD Insights, Azure Synapse Analytics, Azure Data Bricks, CosmosDB, Azure Stream Analytics, Azure Machine Learning Service, R server
Work with business engagement and business stakeholders to understand the requirement, translate them into technical requirements, and partner
Miracle Software Systems, Inc , founded in 1994, is a Global Systems Integrator specializing in ERP/ BPM (EAI/SOA) / B2B / Digital Experience Technologies and is a Minority Certified Private Business headquartered in Novi, MI – USA. Over the past twe... Read More