
Azure Data Engineer
at A Chemical & Purifier Company headquartered in the US.
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Author data services using a variety of programming languages
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- 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 analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centres and Azure regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Work in an Agile environment with Scrum teams.
- Ensure data quality and help in achieving data governance.
Basic Qualifications
- 2+ years of experience in a Data Engineer role
- Undergraduate degree required (Graduate degree preferred) in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases
- Experience with data pipeline and workflow management tools
- Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
- Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
- Strong analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
- Experience supporting and working with cross-functional teams in a dynamic environment

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