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We are looking for a savvy Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

• Implement Azure Data Services and tools to ingest , egress and transform data from multiple sources and create and maintain optimal data pipeline architecture.
• Responsible for creating ETL pipeline with Azure Ecosysem like Azure Synapse ,Azure Data Factory.
• Implement and support ETL related jobs to curate , transform and aggregate data to create models for end user consumption.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• 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 Azure from Sales Force ,Pearson Vue etc.  
• 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.
• Implement the appropriate design patterns while optimizing performance, cost, security, and scale and end user experience.
• 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.
• Maintain ownership of a given pipeline or domain and raise flags to leadership when appropriate regarding architectural concerns.
• Demonstrates commitment to valuing diversity and contributing to an inclusive working and learning environment. 
• Miscellaneous duties as assigned.  

• Ability to build an inclusive culture that encourages, supports and celebrates diversity; serve as a role model to promote DEI best practices.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Strong analytic skills related to working with unstructured datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.

• Bachelor’s degree in computer science or other equivalent degree
• 7+ years of experience in a Data Engineer role.
• Experience with Cloud Data warehouses such as Azure , AWS and Google BigQuery
• Experience with big data tools: Hadoop, Spark and Kafka.
• Experience with Azure Dedicated and Azure Synapse
• Experience with Analytics one or more of the following reporting tools; Tableau, PowerBI, Looker, Domo and Microstrategy
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++,etc.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.

• Up to 5% travel may be required.
• Work normal business hours and extended hours when necessary.
• Remain in a stationary position, often standing or sitting, for prolonged periods.
• Regular use of office equipment in a remote environment such as a computer/laptop and monitor computer screens
• Dexterity of hands and fingers to operate a computer keyboard, mouse, and other computer components

All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic as protected by applicable law. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.