Senior Data Engineer

3 months ago
Full time role
Remote · San Francisco, CA, US... more

Our Mission  

SPAN is enabling electrification for all

SPAN is mission-driven to design, build, and deploy products that electrify our built environment, decarbonize our world, and slow the effects of climate change.

  • Decarbonization is the process to reduce or remove greenhouse gas emissions, especially carbon dioxide, from entering our atmosphere.

  • Electrification is the process of replacing fossil fuel appliances that run on gas or oil with all-electric upgrades for a cleaner way to power our lives.

At SPAN, we believe in:

  • Enabling homes and vehicles powered by clean energy

  • Making electrification upgrades possible

  • Building more resilient homes with reliable backup

  • Designing a flexible and distributed electrical grid

The Role

As a Data Engineer you would be working to design, build, test and create infrastructure necessary for real time analytics and batch analytics pipelines. You will work with multiple teams within the org to provide analysis, insights on the data. You will also be involved in writing ETL processes that support data ingestion. You will also guide and enforce best practices for data management, governance and security. You will build infrastructure to monitor these data pipelines / ETL jobs / tasks and create tooling/infrastructure for providing visibility into these.

Responsibilities

We are looking for a Data Engineer with passion for building data pipelines, working with product, data science and business intelligence teams and delivering great solutions. As a part of the team you:-

  • Acquire deep business understanding on how SPAN data flows from IoT device to cloud through the system and build scalable and optimized data solutions that impact many stakeholders.

  • Be an advocate for data quality and excellence of our platform.

  • Build tools that help streamline the management and operation of our data ecosystem.

  • Ensure best practices and standards in our data ecosystem are shared across teams.

  • Work with teams within the company to build close relationships with our partners to understand the value our platform can bring and how we can make it better.

  • Improve data discovery by creating data exploration processes and promoting adoption of data sources across the company.

  • Have a desire to write tools and applications to automate work rather than do everything by hand.

  • Assist internal teams in building out data logging, alerting and monitoring for their applications

  • Are passionate about CI/CD process.

  • Design, develop and establish KPIs to monitor analysis and provide strategic insights to drive growth and performance.

About You

Required Qualifications

Bachelor's Degree in a quantitative discipline: computer science, statistics, operations research, informatics, engineering, applied mathematics, economics, etc.

  • 3+ years of relevant work experience in analytics, data engineering, business intelligence, research or related fields.

  • Experience in at least one programming language (Python, Scala, or other JVM based languages)

  • Experience working with latency data processing solutions like Flink, Prefect, AWS Kinesis, Kafka, Spark Stream processing etc.

  • Experience with SQL/Relational databases, OLAP databases like Snowflake.

  • Experience in messaging/streaming platforms like Kafka, TimestreamDB etc.

  • Experience working in AWS: S3, MSK, Glue, Athena, EMR, ECR etc.

  • Experience working with CI/CD systems: Circle-CI, Github Actions, Argo-CD, Spinnaker etc.

  • Experience working with IAC providers: Crossplane, Terraform, Pulumi etc.

Bonus Qualifications

  • Experience with the Energy industry

  • Experience with building IoT and/or hardware products

  • Understanding of electrical systems and residential loads

  • Experience with data visualization using Tableau.

  • Experience in Data loading tools like FiveTran

The U.S. base salary range for this position is $134,000- $190,000 plus benefits, equity, and variable compensation for Sales-related roles. This range represents SPAN’s good faith estimate of competitively-priced salary for the role based on national, real-time industry data from companies of a similar growth stage. This range reflects minimum and maximum new hire salaries for the role across US locations. Within the range, individual pay is determined by location and individual factors including relevant skills, experience and education or training. This range correlates to the relative level of the candidate we believe we need for the role and may require an adjustment for candidates of a different level. 

Your recruiter can share more about the specific salary range for the location this role is based during the hiring process. 

Life at SPAN

Headquartered in San Francisco’s vibrant SoMa neighborhood, we are an eclectic group of creative thinkers who value open communication, teamwork, and a ‘make it happen’ approach to addressing complex challenges. 

SPAN embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. 

We’re hiring talented individuals who are driven by success and are passionate about shaping the future of renewable energy. If that sounds like you, we’d love for you to consider joining the rapidly growing team at SPAN.

The Perks:

⚡ Competitive compensation + equity grants at a well-funded, venture-backed company

⚡ Comprehensive benefits: 100% employee premiums for base plans on medical, dental, vision with options for additional coverage.  Parental leave up to twenty four (24)  weeks depending on eligibility

⚡ Comfortable, sunny office space located near BART and Caltrain public transit

⚡ Strong focus on team building and company culture: Employee Resource Groups, monthly social events, SPANcakes recognition breakfast, lunch, and learns

⚡ Flexible hours, one holiday per month, and flexible time off

Interested in joining our team? Apply today and we’ll be in touch with the next steps!