Job Description

Responsibilities

Our Mission

Local Logic is digitizing the built world to make it universally understandable and actionable for consumers, investors, developers, and governments with the ambition of helping build cities that are more sustainable and equitable for the people that live in them.

To achieve that dream, we’ve built a digital twin of cities, quantifying the built world using data and AI to interpret the $217T real estate market throughout the US and Canada.

We started our journey at McGill University’s urban planning department, where we came to see that cities were being developed in all kinds of unsustainable ways. Why were sprawling suburbs still being built, when doing so would increase pollution and inequality? Why were new business parks being built far from mass transit, when doing so would make traffic congestion skyrocket? Why was social housing being built in places that would exacerbate social problems rather than improve them?

It became clear to us why: cities are incredibly difficult to understand. But we realized that with recent advances in data science, all the complexity of cities could be made simple enough for anyone to understand. And that understanding would be essential to making the sustainable, equitable, and prosperous cities that we so desperately need.

Today, Local Logic delivers sophisticated location insights through webtools, APIs, one-click reports and a data analytics platform. Our insights are powered by billions of data points we’ve generated that describe all aspects of cities - from the distance to the nearest bus stop, the quietness on a street, to the most recent trends in the housing market and more.

Your Mission

As a Senior Data Engineer, you’ll be joining the team responsible for building Local Logic’s next generation cloud intelligence platform that is used to create our location-based insights and predictions from large and diverse sources of data. The platform delivers value to our customers through APIs, some exposed externally, and some consumed by our Analytics Platform and our team of data scientists.

You believe in our mission and want to help us achieve it. You bring your own unique perspective to the team, so you can challenge the way we do things for the better. You’re able to speak up when you disagree, ask questions when you don’t understand, and take ownership of your work.

We’re a remote-enabled company, so if you want to work remotely once a week, twice a week, or five days a week, you’ll have all the necessary tools and support you need to do so.

As A Data Engineer, Your Responsibilities Will Include:

• With your incredible technical skills, providing technical leadership and contributing to building our next generation intelligence platform
• Playing a central role in designing and building Local Logic’s cloud-based big data pipelines - we’re processing billions of data points per month
• Using your experience to guide the design and implementation of our data architecture, helping the team make the right tradeoffs to balance cost, scalability and performance
• Mentoring and coaching more junior developers

Key Requirements:

• Strong experience of ETL and generally experience with designing, building, and maintaining data pipelines and maintaining a large scale data ecosystem
• 5+ years of software development experience; startup industry experience is a plus
• Solid programming skills in Python, or other languages such as Scala, Java, etc.
• Experience with distributed compute engines such as Spark, Flink, Dask, etc.
• Experience with cloud Infrastructure (we use AWS)
• Experience with relational databases (such as Postgres, Snowflake, etc.) and NoSQL Databases (Such as Redis, DynamoDB, Cassandra)..
• Knowledge of DevOps methodologies, processes and tools like CDK or comparable frameworks
• Understanding of the challenges that come with building production-grade, scalable, distributed and highly available cloud-based systems and services
• Excellent interpersonal and communication skills
• Ability to embrace change and adapt to shifting priorities
• Think in terms of incremental delivery and experience in Agile development

Additional Preferred Requirements:

• Experience working with geospatial data with tools such as Apache Sedona, Geopandas, etc.
• Experience with Data Analysis libraries such as Pandas, Numpy, Scipy, etc.
• Experience with OLAP servers such as Snowflake, Apache Druid, Redshift, Pinot, and Clickhouse.
• Experience with serverless architectures is a plus
• Experience with orchestration tools such as Apache Airflow, Dagster, Prefect, or AWS Step Functions (We use Airflow)

Why Should You Work Here?

At Local Logic, you have an amazing opportunity to be an early team member of an expanding series A backed startup. We are focused on understanding the world and its cities to predict the future, and make the real estate market more transparent.

We are a people first company that strives to create the best experience for our employees by creating an inclusive, collaborative, challenging environment to learn and problem solve on a daily basis.

You will have access to benefits such as: stock options; comprehensive health, dental and vision plans for you and your family; annual coverage for paramedical services like massage, nutrition and naturopathy; telemedicine service for employees and their families; a culture that emphasizes learning and work-life harmony; mental health awareness day off; weekly yoga session; Headspace (meditation app) membership; unlimited vacation policy; Intentional Fridays; $250 discretionary health and benefits credit.

To support our company value of being Growth Oriented, employees are given a $500 annual professional development credit, as well as 8 hours of professional development time per month. Take the time to develop a new skill, read up on the industry, attend a workshop or conference, or take a short course!

Our Commitment To Diversity & Inclusion

We’re aiming to build a diverse team and inclusive company culture. We are an equal opportunity employer (EOE) and do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

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