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Job Title: Lead Full Stack Data and Analytics Engineer

Location: Remote

Job-Type: 6 month contract to hire

Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).
 

Summary of Position:

The primary mission of the Full Stack Data and Analytics Engineer role is to help our business evolve into an insights-driven organization in which data and analytics drive differentiation in our clients products and customer experiences. The position sits in our Enterprise Data and Analytics team, which aims to drive improved business outcomes using insights gleaned from data and analytics and infuse them into our clients corporate fabric. The Full Stack Data and Analytics Engineer will create innovative data products that deliver insights to business users and drive action, bring DataOps and engineering practices to the analytics team, support advanced analytics development and workflows, and drive the build out of our data fabric that connects data across the enterprise and enables true 360-degree analytics and insights.
 

Principal Duties and Responsibilities:

• Develop and integrate data products, such as published datasets, REST/Graphql APIs, and/or a data marketplace, that deliver information and insights to business users in a modern data stack
• Build, integrate and support the full data and analytics stack that includes the enterprise data warehouse, streaming architectures, the enterprise data catalog and master data management tools
• Drive software engineering and DataOps standards and best practices for data analytics team, including code modularization, versioning, testing, automation/CICD workflows, code reviews
• Partner very closely with the analytics, data product, and data management teams to build and support all core engineering needs across the full data and analytics stack
• Model data from a business perspective
• Develop data analytics tooling to support analysis workflows
• Partner closely with IT product teams to deliver data and insights in a manner that allows business users to understand, interpret, and act within their operational workflows and decision-making processes
• Create intelligent applications that leverage machine learning and artificial intelligence and integrate with IT products
• Instrument data products to enable impact quantification; adoption, quality, business impact
• Work with data/information architects to drive enterprise taxonomy and ontology development to connect disparate data across enterprise and enable 360 insights
• Gain an understanding of core business processes and align data development with business strategy
• Wrangle and integrate data from disparate systems to allow data analysts and data scientists leverage to end-to-end data and information
• Develop data science workflows to optimize artificial intelligence lifecycle

Education and Experience Requirements:

• Master’s degree preferred (desired in relevant area), or multiple certifications
• 7-10+ years progressive work experience in related fields
• 4-7+ years as a full stack developer and 2-4+ years in developing end-to-end data and analytics products, years of experience may be concurrent
• Expertise across the ‘modern data stack’ – Snowflake, dbt, Fivetran, Airbyte, Prefect, NoSQL, and similar tools and technologies
• Ability and willingness to quickly learn new technologies
• Demonstrated ability to deliver end-to-end data products that put information and insights into the hands of business users
• Expertise in core software engineering principles (code modularization, versioning, git, testing, CICD, Agile etc.)
• Expertise in SQL and RDBMS; Experience working with NoSQL database systems
• Strong Proficiency in programming languages used in data science, such as Python and R
• Expertise in cloud (Azure, AWS) data ecosystem and workflow automation technologies
• Expertise in data wrangling and integration
• Demonstrated ability to develop data science workflows
• Experience with semantic data modeling and knowledge graphs
• Experience building out the enterprise data fabric according to its prescribed information architecture
• Experience working with product teams and business users to understand how to optimally deliver insights within their operational workflows and decision-making processes
• Demonstrated ability to quantify/measure impact of actions taken based on insights
• Thirst to help transform our client into an insights-driven organization
• Ability and willingness to learn about the business, its strategy, objectives, and core business processes
• Proficiency in semantic modeling, and knowledge and ontology engineering (preferred)

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