Full-Time
Quantitative Sales Associate
Posted on 6/27/2024
Databento
11-50 employees
Pay-as-you-go market data platform
No salary listed
Salt Lake City, UT, USA + 3 more
More locations: Boston, MA, USA | San Francisco, CA, USA | New York, NY, USA
Hybrid
 Finance & Banking (3) |
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- Own the technical sales process, from answering technical customer inquiries and providing data samples to solving data-related issues that our customers raise.
- Create common examples and use-cases with market data, with examples in Python, C++, and/or Rust.
- Gather customer feedback, testimonials, case studies, and more.
- Establish and maintain accurate, timely, and documented forecasting and record-keeping procedures, keeping our CRM up-to-date and organized.
- Build a network of executive relationships across the industry and with key partners and customers.
- Stay up-to-date with industry trends, market dynamics, and competitor activities to identify potential business opportunities and adapt sales strategies accordingly.
- Collaborate across teams to align sales efforts with overall company objectives and ensure a seamless customer experience.
- Understand and communicate with our user base of developers and quants.
- Experience with quant trading and market microstructure.
- Extreme attention to detail and record-keeping, as well as the ability to automate processes in HubSpot.
- Professional communication skills that align with the tone of an institutional financial product.
- White-glove management of the sales cycle with continual buy-in from the customer, discovering the user's pain points, signs of friction, being honest when our product isn't the best fit, not being too pushy or salesy, and knowing when to continue vs. back off.
- Readiness to work within a startup environment with limited resources and personnel.
- As a bonus: Active usage of GitHub, knowledge of enough C++, Python, and/or Rust to help answer client inquiries.
Databento provides a self-service platform that makes market data easy to access by offering instant live exchange feeds and access to terabytes of historical data on a pay-as-you-go basis. Users can get data on demand and only pay for what they use, without long-term contracts. The platform is designed for a wide range of users—from large finance and fintech firms to small startups—who need fast, scalable access to data. How it works: users sign in to the platform, choose the data feeds they need (live or historical), and pay based on usage, enabling on-demand data access via a self-service interface. How it differentiates itself: it combines immediate, on-demand data access with a transparent, usage-based pricing model and a team with extensive experience in high-frequency trading and financial technology, targeting both big institutions and smaller players. Its goal is to simplify and accelerate market-data access, helping customers move faster and reduce data costs.
Company Size
11-50
Company Stage
Series A
Total Funding
$66.1M
Headquarters
Boston, Massachusetts
Founded
2019
Simplify's Take
What believers are saying
- Major quant hedge fund selected Databento as primary options data provider in 2025.
- Databento achieved 4.2x GAAP revenue growth and 187% user base expansion past year.
- QuantConnect LEAN integration on April 17, 2026, expands access to 100k+ algo traders.
What critics are saying
- Live API changes on April 26, 2026, cause data gaps and crashes for 20-30% users.
- SEC CAT feeds by Q4 2026 commoditize US Equities datasets, slashing demand 40-60%.
- dxFeed's Rust SDK outperforms Databento by 10-20 microseconds, capturing HFT firms.
What makes Databento unique
- Databento delivers 590-microsecond median latency from matching engine over public cloud.
- Databento sources L3 data directly from NY4, Aurora I colocation without third-party providers.
- Databento offers self-service APIs in Python, C++, Rust for 15 exchanges and 30 ATSs.
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Benefits
Health Insurance
Dental Insurance
Life Insurance
Disability Insurance
401(k) Company Match
Remote Work Options
Growth & Insights and Company News
6 month growth
↓ -5%1 year growth
↓ -5%2 year growth
↓ -8%Upcoming changes to the live API. March 24, 2026 On Sunday, April 26, 2026, Databento, Inc. is rolling out two updates to the live API: These changes aim to reduce perceived latency and improve developer experience, but may introduce breaking changes for some customers. Details for each change are outlined below, including how to continue using the current behavior if preferred. When a live client processes records more slowly than the gateway sends them - for example, during periods of high message throughput - the gateway detects that the session has fallen behind real time. The slow_reader_behavior parameter determines how the gateway handles this and can be set to warn or skip when creating the client. * warn: The gateway continues sending all records and periodically sends a SystemMsg with code = SlowReaderWarning (2) while the client is behind. * skip: The gateway drops records until the session is current, then sends an ErrorMsg with code = SkippedRecordsAfterSlowReading (7) before continuing in real time. Currently, the default behavior is warn for all schemas, which means the gateway buffers and sends stale records until the client catches up. This can increase observed latency, measured by the difference between the ts_out (send) and ts_recv (receive) timestamps. This behavior is often undesirable for stateless schemas, where each update already reflects the latest state at that point in time (e.g., best bid and offer or aggregated depth). As a result, skipping stale records and returning to real time is typically preferred. For these schemas, the default value of slow_reader_behavior will change from warn to skip: MBP-1, CMBP-1, MBP-10, BBO-1s/1m, and CBBO-1s/1m. All other schemas are unaffected and will continue using warn as the default since dropping records may result in missed events or gaps in the data. To continue using warn for the stateless schemas listed above, set the slow_reader_behavior parameter to warn when creating the live client. The following examples demonstrate this in Python, Rust, and C++. import databento as db client = db.Live(slow_reader_behavior="warn") use databento::{LiveClient, live::SlowReaderBehavior}; let client = LiveClient::builder .key_from_env? .slow_reader_behavior(SlowReaderBehavior::Warn) .build .await?; #include <databento/enums.hpp> #include <databento/live.hpp> namespace db = databento; auto client = db::LiveBlocking::Builder .SetKeyFromEnv .SetSlowReaderBehavior(db::SlowReaderBehavior::Warn) .BuildBlocking When subscribing to live data, each symbol specified in the symbols parameter is resolved (matched) to one or more instruments in the dataset. Currently, if any symbols don't exist, they fail to resolve, and the gateway closes the session. Subscribing to an invalid symbol will no longer automatically terminate the session. The gateway will still send an ErrorMsg record for each symbol that fails to resolve, but any available symbols will be streamed. If none of the requested symbols resolve, the session will remain open, but no data will be received. This has been a common request, especially for workflows involving weekly and daily options, where symbols change frequently as contracts are listed and expire. To continue treating unresolved symbols as a failure, ensure your client terminates the session when an ErrorMsg with code = SymbolResolutionFailed (4) is received.
Introducing ICE Europe Financials. Databento, Inc. is excited to announce that ICE Europe Financials is now available on Databento, with real-time data and over 7 years of historical coverage. ICE Europe Financials is sourced from ICE's proprietary iMpact feed and captures full order book depth, market statistics, and reference data for all financial futures and options listed on ICE Futures Europe. Users can access the data in L1, L2, or L3 granularity, as well as other formats. A complete list of supported schemas is available in its catalog. ICE Europe Financials covers derivatives on interest rate and equity index products. This dataset includes: * Short-term interest rate futures (STIRs) on benchmarks like Euribor, SONIA, and SOFR. * Swapnote contracts for interest rate swap exposure without physical delivery. * Government bond futures, including Long, Medium, and Short Term Gilts. * Equity index derivatives such as FTSE 100 futures and London Stock Exchange options. Commodity derivatives from ICE Futures Europe are available in the ICE Europe Commodities dataset. ICE Europe Financials data can be requested using its dataset ID: IFLL.IMPACT. Visit its pricing page to explore subscription plans starting at $199/month. Historical coverage begins on December 23, 2018. Data is available at usage-based rates or included with a flat-rate subscription. The example below demonstrates how to request one day of trades data for FTSE 100 Index futures using its Python client library. Real-time access is available with a Plus or Unlimited plan. The example below demonstrates how to stream trades data for three-month Euribor futures.
Databento, Inc. is excited to announce the addition of real-time Cboe EDGX Depth data to Databento US Equities.
Databento, Inc. has launched new subscription plans for its OPRA service.
Main Set, the Fintech-focused venture capital firm, has secured commitments of £14 million for its inaugural fund, after launching in late 2024. Anchored by Capricorn Capital Partners, the fund is targeting £40 million by final close, dedicated to partnering with category-defining Fintech and adjacent SaaS businesses.This milestone marks the next phase of Main Set’s evolution, building on the firm’s successful investment-by-investment approach to raising its first blind pool of capital. The fundraise reflects the growing optimism surrounding Fintech in 2025 and beyond, appealing directly to LPs seeking exposure to high growth innovative companies within the space.Speaking on the announcement, Ioto Iotov, Founder and Managing Partner of Main Set said “We’re excited by the interest in our growing platform, bringing additional capital to our deployment capabilities at a time where the pipeline of high quality Fintechs is incredibly strong. We appreciate the support of existing and new investors, and will continue to follow our disciplined investment process as we capitalise on the investment opportunity in these large and fast growing verticals.Main Set’s four active portfolio companies, Anyfin, Sprout.ai, WealthOS, and Databento, will form a seed portfolio for the fund, putting capital to work early and shortening expected routes to liquidity for fund investors.Leveraging a systematic, data-driven investment approach, Main Set builds conviction through the identification of innovative solutions to clearly defined challenges, demonstration of sound business models, unit economic analysis and recognising their substantial potential for growth over the coming years.Main Set actively supports portfolio companies beyond capital, leveraging its team’s Fintech expertise across Payments, Insurtech, Wealthtech, Office-of-the-CFO tools, and Neobanking / Neolending. This hands-on approach accelerates portfolio companies’ growth in a purposeful, sustainable way.“Anyfin operates in a field that to many investors is not intuitive, making it a delight to meet people who understand the business model, market dynamics and what it takes to win in Fintech. Ioto and the Main Set team have been value-additive partners since investing, who understand what it takes to achieve success.” – Mikael Hussain, Co-Founder and CEO, AnyfinAlongside its core team, Main Set is supported by a growing network of eight venture scouts and a dedicated venture partner — all seasoned Fintech and Financial Services professionals aligned with the fund’s specialist verticals