At Convex (YC W19), we’re building the leading B2B full-stack software platform for the $400bn+ commercial services market. It's a 100-year-old industry impacting millions of people every day. We already work with some of the largest enterprise companies in the sector and were one of the fastest growing companies in the Winter 2019 YC batch. Our team is a unique mix of industry veterans from Carrier, Siemens, and Honeywell as well as founders from MIT, Harvard, and Georgia Tech. Based in San Francisco, our investors include Emergence Capital, 1984 Ventures, UP2398, Liquid2 (Joe Montana), Y Combinator, the founders of PlanGrid, and others.
At Convex, we build the leading B2B platform for the fast growing commercial and building services industry. Our software provides rich data on every commercial property in the US (~63M) and workflow software built on top of that. For our users who serve these properties, that data and workflow becomes their secret weapon; there's nothing else like it available in the market today. Our customers rely on Convex to identify, win, and manage new growth opportunities.
We are based in, and love, the seven square miles of San Francisco, but our customers (and employees) live and work in almost every state in America. They include some of the largest enterprises in the country, like Siemens and Carrier, and smaller businesses we care just as deeply about.
We are looking for an experienced Data Engineer / Data Architect to build scalable platforms that enable efficient data movement within Convex across various sources, sinks, and support continuous data integration and processing with external enterprise systems via secure APIs and connectors.
You will have a chance to:
Design and implement reusable solutions and architectures for data sharing and processing use cases
Support and improve our multi-tenant data pipeline, processes, infrastructure, and stack
Drive end-to-end performance, scaling, observability, and monitoring of our platforms
Create data governance models, including assets, relationships, domains, and communities
Work in the heart of a business with multiple partner teams to build cross-functional customer solutions
You have the following qualifications:
Bachelor’s degree in Computer Science or related technical field or equivalent practical experience
5+ years of software backend/data engineering experience, including familiarity with data modeling, ETL, schema and system design, roadmap planning, batch processing, implementation, maintenance, and documentation
Professional development experience in languages such as Python, Scala, Java, Go, etc.
Experience with large-scale distributed storage and database systems (e.g. Postgres, ElasticSearch, Cassandra, Hadoop, etc)
Sound knowledge about database concepts such as transactions, indexing, concurrency
Effective communicator; able to help drive data engineering roadmap and keep stakeholders updated
It would be nice if you have:
Masters or Ph.D. in Computer Science or related field
Experience building geospatial services and datasets, such as maps data
Hands-on experience building Spark applications or similar Big Data pipelines / frameworks / services (e.g. Hadoop, Hive, Kafka, Presto, Beam, Parquet, Avro etc.)
Familiarity with API integrations and development on respective CRM platforms
Understanding of data science & machine learning use cases
Generous employer contributions towards medical, dental, and vision insurance
Paid parental leave of up to 4 months with 100% pay
Flexible & generous time-off plans (including mental health days!)
Income protection through short-term and long-term disability plans
Tax-favored benefits such as Retirement Savings plans and Flexible Spending Accounts
Healthy lunch, drink, and snack options at our corporate office
Flexible hybrid & remote work options
At Convex (YC W19), we’re building the leading B2B full-stack software platform for the $400bn+ commercial services market. It's a 100-year-old industry impacting millions of people every day. We already work with some of the largest enterprise companies in the sector and were one of the fastest growing companies in the Winter 2019 YC batch. Based in San Francisco, our investors include Fifth Wall, Emergence Capital, GGV, 1984 Ventures, UP2398, Liquid2 (Joe Montana), YCombinator, the founders of PlanGrid, and others.
At Convex, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us!
Convex is an equal opportunity employer and values 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.
If you need assistance or an accommodation due to a disability, please let your recruiter know.
Convex is looking for engineers to help our customers serve an under the radar, but massive and ubiquitous industry, commercial building services. Our customers service the systems that provide air we breathe, the water we drink, as well as the lighting, safety, and security systems that power daily life for billions of people.
We are based in, and love, the seven square miles of San Francisco, but our customers are in every corner of America. We found our foothold in small to medium sized businesses, and have quickly been pulled up-market to some of the largest enterprises in the country, like Siemens and Carrier. We have shipped an impressive amount of product with a lean team, but now we have to scale to meet the demands of our customer base which is growing in both size and sophistication.
That is why we need you.
Our flagship product, Atlas, is a “consumer grade enterprise product.” Think Apple experience with Oracle utility. Atlas supercharges our users’ work by providing them with information on virtually every commercial property in the country. There is literally no other data source like this available anywhere. All that data is interesting, but it isn’t powerful unless you have the ability to work with it, which is why we are building a full suite of specialized software tools on top of it.