Data Engineer

  • Inspire Clean Energy
  • Remote
  • Oct 09, 2021

Job Description

ABOUT US

Inspire is a clean energy technology company on a mission to transform the way consumers access clean energy and to accelerate the world’s transition to a net-zero carbon future.

We provide our customers with access to renewable energy from wind, solar, and hydro powered sources without service interruptions or costly installations at a flat, predictable monthly rate. For every year that a customer spends with Inspire Clean Energy, they have a greater impact on climate change than 10 years of strict recycling.

Our rapidly growing team of mission-driven, climate enthusiasts is passionate, innovative and committed to a better future for the planet.

POSITION SUMMARY

As a Data Engineer on Inspire’s Data & Analytics Engineering 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. In this position you will collaborate with partners across the business in a shared mission to achieve a clean energy future.

THE DATA ENGINEER HAS 4 MAIN RESPONSIBILITIES

  • Shared ownership and accountability for Platform data services (fivetran, Airflow, dbt, Snowflake) through deep knowledge and proactive maintenance of those services
  • Guide and execute architectural improvements to our data services
  • Communication skills, and ability to translate between the domains of business problems and technical solutions
  • Team-oriented development: building modular & re-usable tools, writing maintainable code, team mentorship, owning technical and business documentation

SOME YEAR 1 DELIVERABLES

  • Expand the capabilities of Inspire’s core data platform to support incremental business lines and product features
    • Productionizing our Operating Model and Machine Learning infrastructure
    • Refactoring Platform services for CNNG
    • Platform improvements to enhance digital and direct acquisition of customers
    • Improving data quality and observability within our data infrastructure
  • Partner with Technology and Member Operations 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

  • Challenge the status quo - we're looking for someone with enough experience in data engineering to have begun forming strong opinions of data best practices. Those opinions should surface in their work and at times challenge Inspire’s data practices to raise them to new standards. In the process, their opinions should stimulate growth and learning throughout the team.

EXPERIENCE

  • Must Have
    • 3+ years of experience in a data engineering role
    • Strong SQL skills querying and transforming large datasets in cloud-based data warehouses (we use Snowflake)
    • Experience creating production-grade ELT pipelines with python-based data orchestration tools at scale (we use Airflow)
    • Software development lifecycle experience in GitHub (i.e. environment management, testing, deployment)
  • Nice to Have
    • Experience with real-time event stream data
    • Experience with dbt
    • Spark data processing
    • ML Flow infrastructure
    • Contextual work in the energy industry

Organization Type

Company

Organization Size

101-250

Sectors

Carbon Accounting & Offsetting, Energy, Pollution & Waste Reduction

Network:

New Energy Network