Data Engineer

at  TapestryHealth

Data Engineer
Job Overview
We are looking for a savvy Data Engineer to join our growing development team. 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 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.

Responsibilities for Data Engineer

• Create and maintain optimal data pipeline architecture, define and maintain ETL
• 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 SQL and Azure cloud 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 multiple data centers.
• 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.

Qualifications for Data Engineer

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing data pipelines, architectures and data sets.
• Experience with programing to develop and code ETL.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• We are looking for a candidate with 3+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
• Experience with Database Administration/Maintenance
• Experience with big data tools, distributed SQL: Azure Data Factory/Synapse.
• Experience with relational SQL (NoSQL useful), including Postgres and SQL Server.
• Experience with Analytics Tools: Power BI
• Experience with Microsoft Azure cloud services
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, Go, etc.

• Create and maintain optimal data pipeline architecture, define and maintain ETL
• 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 SQL and Azure cloud 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 multiple data centers.
• 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