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Senior Data Engineer

Who we are: First Street is the industry standard for physical climate risk data. We use transparent and peer-reviewed methodologies to calculate the past, present, and future climate risk for every property in the world. We started eight years ago by working with the world’s leading climate scientists to create groundbreaking, climate-adjusted, property specific models and haven’t stopped. 

Our mission: We exist to connect climate change to financial risk

Our data: We create physics-based, deterministic models of flooding, wildfire and hurricanes, and advanced statistical models of extreme heat, air quality, drought, hail, severe convective storms, winter storms, and more. All of this data is used to create property-level financial risk metrics and macroeconomic variables to quantify the impacts of climate change. 

Our customers: We empower governments at the highest levels to make smart regulations, businesses to avoid bad investments, and everyday Americans to understand their personal risk from climate change. We are relied on every day by:

  • Agencies ranging from the U.S. Department of Treasury to Fannie Mae

  • The world's biggest banks such as Bank of America and Wells Fargo 

  • Institutional investors like Nuveen and Blackstone 

  • Millions of users on Redfin, Realtor.com, Homes.com, and more 

We believe:  Our work needs to match the pace and scope of the climate problem. This is why we have invested tens of millions of dollars into our science, data, people, and products and have raised tens of millions more to move even faster.  Read more about our culture here.

Come join us and use your talents to create solutions to address humanity's biggest problem.

Team & Role Overview 

We are looking for a Senior Data Engineer to join our team. The successful candidate will be someone who deeply cares about the environment, loves information technology, and appreciates the importance of data for the success of the First Street mission. They will assist in the ingestion of climate risk and ancillary data from First Street modelers and data partners, develop data pipelines, query geospatial databases, calculate applicable statistics, implement Quality Assurance and Quality Control processes, utilize geographical imagery, and ensure that the Data Team’s databases and pipelines are coordinated and synchronized with the Software Engineering Team’s databases, APIs, and web services. This individual will be responsible for developing data operations across the Data Team, and through their expertise and leadership generally enabling all members of the Data Team to be successful in their roles.

What you’ll do: 

  • Provide technical support in the processing, analysis, and interpretation of geospatial observations and modeling data.

  • Develop and implement processes for processing large volumes of hazard prediction data to improve risk assessment quality and accuracy.

  • Plan, execute and direct Unix-based workflows on local and cloud-based clusters, using GDAL, PostgreSQL, Python and related technologies.

  • Analyze raster and vector data at scale to improve model accuracy, identify quality control issues, and develop suggested remedies for identified issues.

  • Perform statistical analysis to validate hazard model predictions and assess model uncertainties.

  • Design and implement quality assurance checks on the climate risk data and derived statistics

  • Assist in resolution of customer support issues through quality control checks and explanation of the models and risk statistics

What you’ll need: 

  • Bachelor's Degree in Data or Climate Science, or a related Field  

  • 3+ year of professional experience 

  • Data operations: Experience with the design, and use of databases, such as PostgreSQL

  • Programming: Proficiency with SQL queries to efficiently and reproducibly analyze complex datasets preferred. Additional languages like Python or R also required

  • GIS knowledge: Experience with writing software to efficiently process and analyze with geospatial data using open source tools

  • Strong understanding of probability and statistics as applied to spatial data

  • Expertise using scripted languages to build data pipelines on both local and cloud-based systems

  • Experience with big data analysis, parallel processing, and batch/spot workflows on cloud platforms including AWS, GCP, and/or Azure

  • Proficiency with source control platforms such as Git

  • A science-based approach with a high degree of concern for reliability, accuracy and reproducibility

  • Experience in GIS and/or geospatial statistical analysis

What will make you stand out: 

  • Previous experience in the physical sciences 

  • Masters Degree Preferred

How we work: 

  • Impact: We only focus on things that move the needle 

  • Drive: We are driven by the role we play in connecting climate change to financial risk 

  • Ownership: This is our company and we act accordingly

  • Urgency: We move quickly because the world depends on it 

  • Resilience: We have a growth mindset in all that we do

What we offer: 

  • Competitive salary commensurate with experience 

  • Ownership interest in the company via Employee Stock Option Plan 

  • Hybrid Schedule with in-office work days on Monday, Wednesday and Thursday 

  • 15 vacation days along with 13 company holidays and 10 sick days 

  • Health benefits covered at 100% for employee or a significant contribution for family plans 

  • Vision and dental benefits with partial employee contribution

  • 12 weeks of paid parental leave 

  • Access to One Medical, Teledoc, HealthAdvocate, Kindbody, and Talkspace

  • Company 401k program 

  • Commuter benefits 

  • Life Insurance

  • Tech startup environment 

  • Weekly team meals and an office stocked with coffee and snacks 

  • Working on the world’s biggest issue with other passionate professionals 

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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Average salary estimate

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What You Should Know About Senior Data Engineer, First Street

At First Street, we're on a mission to connect climate change to financial risk, and we're looking for a skilled Senior Data Engineer to join our passionate team in New York City. If you're someone who cares about the environment and understands the significance of data in driving impactful solutions, this role is perfect for you. As a Senior Data Engineer, you will play a crucial part in ingesting climate risk data and collaborating with modelers and data partners. You'll develop sophisticated data pipelines, manage geospatial databases, and implement quality assurance processes to ensure our models are precise and reliable. Your role will also involve handling large volumes of data, using technologies like PostgreSQL, Python, and GDAL, as well as statistical analysis to validate predictions. Working in sync with our Software Engineering Team, your contributions will empower us to create the most reliable risk metrics out there, impacting the way governments and institutions understand climate risk. If you’re ready to work on one of humanity's biggest challenges while developing advanced data operations, we would love to hear from you. Imagine contributing to innovative solutions that guide everyday Americans and government agencies in navigating financial risks associated with climate change. Join us at First Street, where your talents can shine and make a real difference for the planet!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at First Street
What are the responsibilities of a Senior Data Engineer at First Street?

A Senior Data Engineer at First Street is responsible for ingesting climate risk data, developing data pipelines, and conducting statistical analysis to ensure the accuracy of risk assessments. They also implement quality assurance processes, manage geospatial databases, and collaborate with the Software Engineering Team to synchronize databases and workflows.

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What qualifications do I need to become a Senior Data Engineer at First Street?

To become a Senior Data Engineer at First Street, you should have a Bachelor's Degree in Data or Climate Science, or a related field, along with at least 3 years of professional experience. Proficiency in SQL, experience with geospatial data processing, and a strong understanding of statistics, particularly in relation to spatial data, are essential qualifications.

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What technologies should a Senior Data Engineer at First Street be familiar with?

A Senior Data Engineer at First Street should be familiar with technologies including PostgreSQL for databases, Python or R for programming, GDAL for geospatial data processing, and cloud platforms like AWS, GCP, or Azure for big data analysis and workflows. Experience with source control platforms like Git is also important.

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How does the Senior Data Engineer role contribute to First Street's mission?

The Senior Data Engineer plays a pivotal role in First Street's mission by developing data pipelines that enhance the accuracy and reliability of climate risk metrics. Their work enables timely and precise assessments that empower governments, institutions, and individuals to make informed decisions about climate-related financial risks.

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What is the work environment like for a Senior Data Engineer at First Street?

The work environment for a Senior Data Engineer at First Street is dynamic and collaborative, set in a tech startup atmosphere. The team values impact, ownership, and resilience, fostering a culture where quick decision-making and continuous learning drive success in addressing the challenges posed by climate change.

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Common Interview Questions for Senior Data Engineer
Can you explain your experience with geospatial data processing as a Senior Data Engineer?

When discussing your experience, highlight specific projects where you utilized tools such as GDAL or PostgreSQL for geospatial data processing. Explain the context and your role, emphasizing how your contributions improved data accuracy or efficiency in risk assessments.

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How do you ensure the quality and reliability of data in your projects?

To ensure the quality of data, discuss your approach to implementing quality assurance checks and validation processes. Provide examples of statistical methods you've used to verify model predictions and rectify any discrepancies.

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What programming languages are you proficient in, and how do you use them as a Senior Data Engineer?

Mention your proficiency in languages like Python or SQL, detailing how you've used these languages to build data pipelines, analyze complex datasets, and perform geospatial analysis. Elaborate on specific tools or libraries that facilitated these tasks.

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Describe a challenge you faced in past data engineering projects and how you overcame it.

When presenting a challenge, be specific about the problem and the context. Discuss your analytical approach, the solutions you proposed, and the positive outcomes that resulted from your efforts. This demonstrates your problem-solving ability and resilience.

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How do you approach statistical analysis for validating model predictions?

Your answer should outline your methodology for conducting statistical analysis, including the techniques you use to assess model performance. Offer examples of metrics or tests you apply to ensure model reliability, demonstrating your analytical skills.

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What is your experience with cloud platforms and big data analysis?

Discuss your hands-on experience with cloud platforms like AWS or Azure and the techniques you employed for big data analysis. Share insights about specific projects you worked on that involved parallel processing or batch workflows.

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How do you stay current with advancements in data engineering and geospatial analysis?

Talk about your strategies for staying updated, such as attending workshops, webinars, or conferences. Mention any relevant publications you follow or communities you engage with to continuously enhance your knowledge and skills.

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What contributions can you make towards First Street's mission?

Reflect on how your background and experience align with First Street's mission. Highlight your commitment to climate change solutions, your data engineering expertise, and how you envision helping the team create impactful and accurate climate risk assessments.

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Can you provide an example of a successful data pipeline you built for project needs?

Outline the project scope and the requirements laid out for the data pipeline. Describe the technologies and methodologies you implemented and the positive impact it had on data accessibility or performance, showcasing your technical talents.

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What motivates you to work in the field of data engineering and climate risk?

Express your passion for both data engineering and environmental issues. Explain how the intersection of technology and climate science excites you and motivates your desire to contribute to solutions that tackle pressing global challenges.

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Full-time, hybrid
DATE POSTED
December 21, 2024

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