Design and develop business-critical backend systems using stream processors and high-quality data pipelines.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure 'big data' technologies.
Build a cloud-native, real-time stream processing & data lake platform that scales into the Zettabytes and beyond.
Build a data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Ability to automate data pipelines using DevOps tools.
Perform root cause analysis on external and internal processes and data to identify opportunities for improvement.
Build processes that support data transformation, workload management, data structures, dependency, and metadata.
Adopt for change, always open to replacing what you built yesterday with something better today.
Work with all stakeholders to design and code large-scale batch and real-time data pipelines on Azure.
Perform code reviews, and lead by example on code refactoring for readability, extensibility, and testability.
Requirements
A bachelor's degree in computer science or equivalent
4+ years of experience as a Data Engineer,
Experience with Azure big data tools: Azure Databricks, Azure Synapse, HDInsight, ADLS
Experience with relational SQL and NoSQL databases.
Excellent problem solving and analytic skills associated with working on structured and unstructured datasets using Azure bigdata tools.
Experience with data pipeline and workflow management tools: ADF and Logic Apps