Data Engineer

POSITION SUMMARY

As a Data Engineer on Inspire’s Data Platforms and Services team, you will build, maintain, and improve the infrastructure and architecture that flows critical data from internal and external sources to where it creates value for the business. We take a product-driven, agile approach to our platform, driving measurable growth and meaningful outcomes every single sprint. We build efficient, scalable processes in a service-oriented ecosystem leveraging powerful code frameworks and repeatable patterns to solve real problems for stakeholders and customers. 

THE DATA ENGINEER HAS FOUR MAIN RESPONSIBILITIES

1. Data querying and processing in SQL
2. Data processing and task management in Python
3. Communication skills, and ability to translate between the domains of business problems and technical implementations
4. Team-oriented development: building modular & re-usable tools, writing maintainable code, owning technical and business documentation

SOME YEAR 1 DELIVERABLES

• Refactor operating model code into scalable, transparent processes leveraging Airflow and DBT as core frameworks
• Expand the capabilities of Inspire’s core data platform to support incremental product lines and product features
• Partner with Analytics to systematize and scale high-integrity value-oriented analysis
• Partner with Sales, Operations, and other business stakeholders to design and deliver new data-driven integrations
• Partner with other engineering teams to guide refactors of existing data infrastructure to improve data quality and features.

SUCCESS METRICS

• Cultivated familiarity with Inspire’s frameworks & operating model
• Delivery of high-quality pull requests in DBT and Airflow, evidencing strong code standards & testing practices
• Comfort with self-directed project management: requires minimal oversight to assess a problem, formulate a solution, deliver code, and document changes.
• Positive interactions with department stakeholders: can offer guidance and input that creates business value for non-technical personnel.

DESIRED TRAITS

• Technical competency - comfort on a command line, a good grasp on the fundamentals of programming, a general understanding of Git/source control, and a willingness to read the docs, search stack overflow, and test it until it works
• Problem-Solving Mentality - gets excited about digging into complexity, wants to ask questions and learn more, and isn’t put off by problems they’ve never been explicitly told how to solve. Especially troubleshooting: ability to break down a chain of steps to narrow and locate a problem.
• Number Sense - Strong background in mathematics or physics, comfort with quantitative measurement and estimation. Ability to work in establishing boundaries and orders-of-magnitude to make informed judgements without fussing over exactitude.
• Big-picture awareness - Understanding of the importance of context, and willingness to understand the business problem in addition to the technical one. Focus on people & impact.

EXPERIENCE

• Must Have
  • 1 or more years in a data analytics, engineering or science role
  • Strong SQL experience working with large datasets, ideally in cloud-based data warehouses
  • Software development in Python3
  • Experience automating data processing, cleaning and/or preparation
  • Software development lifecycle familiarity in GitHub (ie environment management, testing, deployment)
• Nice to Have
  • Experience with key frameworks: Snowflake, Apache Airflow, dbt, AWS services, Docker, Kubernetes
  • Experience at a similar scale of data processing (Multi-TB/billions of rows)
  • Work with real-time event stream data
  • Contextual work in the energy industry
  • Data consultancy experience a plus
  • Proven ability to break down a chain of steps to narrow and locate a problem
  • Strategic approach to problem solving and understand the why behind a problem