Data Engineer

Olo is a leading SaaS platform accelerating digital transformation in the restaurant industry, by helping customers deliver more personalized and profitable guest experiences. As a result, our digital ordering, payment, and guest engagement solutions enable hospitality at scale, helping brands to do more with less, and making every guest feel like a regular.

We are looking for a collaborative and driven data engineer who thrives at the intersection of problem-solving, data architecture, and innovation. The ideal candidate is skilled in designing and building scalable data pipelines, enjoys working with complex datasets, and has a keen interest in empowering both internal teams and external customers through actionable insights. As a Data Engineer at Olo, you will play a pivotal role in building and maintaining cutting-edge data pipelines that bridge online-to-offline transactions. You'll work on developing guest-centric metrics dashboards and integrating data from diverse sources to help us unlock new insights into guest behavior, both online and in-store. We want people who are passionate about creating solutions that empower businesses and elevate guest experiences.

Reporting to the Data Engineering Manager, the Data Engineer will collaborate closely with cross-functional teams, including analytics, product, and external customer stakeholders. You will design, implement, and optimize robust data workflows that enable our customers and internal teams to make smarter, faster decisions.. This is more than a data engineering role—it’s an opportunity to shape the future of how businesses and consumers interact. By joining our team, you’ll be contributing to innovative solutions that provide a unified view of guest transactions across online and offline channels. Your work will not only be integral to Olo’s strategic initiatives but could also redefine industry standards in digital commerce. This is your chance to work on projects that are not just exciting but have the potential to make a lasting impact.

You can work remotely from anywhere in the U.S. or at Olo’s headquarters in NYC.

• Design and implement ELT processes and data models using dbt.
• Design and maintain data orchestration workflows using Dagster or Airflow.
• Build data pipelines to support machine learning use cases, enabling predictive and prescriptive customer facing inference.
• Build and optimize processes for sourcing, processing, contextualizing, and modeling data.
• Create and maintain near-real-time streaming data pipelines.
• Deliver automated solutions to address complex data processing challenges.
• Enforce data retention policies to balance liability, cost efficiency, and data lifecycle optimization.
• Develop and maintain a comprehensive data catalog, dictionary, and technical documentation derived from data assets and software solutions.

• 2+ years of experience in the development of one or more of these technologies: Database solutions, data pipelines, advanced analytics applications
• 2+ years of experience with one or more of these datastores: Snowflake, Redshift, Teradata, Azure Synapse (SQL Data Warehouse), BigQuery, Hadoop, Microsoft SQL Server, PostgreSQL, other leading RDBMS
• Advanced proficiency in SQL (any dialect)
• Adequate knowledge of at least one programming language, ideally one widely used in the data industry, such as: Python, Spark, Scala
• Thorough understanding and application of data modeling principles

About Olo

Olo (NYSE: OLO) is a leading restaurant technology provider with ordering, payment, and guest engagement solutions that help brands increase orders, streamline operations, and improve the guest experience. Each day, Olo processes millions of orders on its open SaaS platform, gathering the right data from each touchpoint into a single source—so restaurants can better understand and better serve every guest on every channel, every time. Over 700 restaurant brands trust Olo and its network of more than 400 integration partners to innovate on behalf of the restaurant community, accelerating technology’s positive impact and creating a world where every restaurant guest feels like a regular. Learn more at olo.com.

We’re remote-friendly. Since 2015, we have been evolving our culture to continue to support a more distributed workforce and now over 75% of our team works remotely across the U.S. If you're in the New York City area, you can choose to work remotely or from Olo's headquarters, on the 82nd floor of One World Trade Center.

We offer great benefits, such as 20 days of paid time off, 10 separate sick days, 11 holidays, plus year-end closure, health, dental, and vision coverage for yourself and your family, a 401k match, remote-office stipend, company equity, a generous parental leave plan, volunteer time off, gift matching policy, and more!

Our best estimate of the compensation range for this opportunity is $88k-120k annually for a Data Engineer I and $105k- 140k annually for a Data Engineer II, depending on the experience you bring and your location. We look forward to discussing your salary expectations and our full total rewards offerings throughout the interview process.

We encourage you to apply!

We value diversity. At Olo, we know a diverse and inclusive team makes our workplace better. Don't meet every single qualification in the job description? Market data shows that women and people of color are less likely to apply to jobs unless they meet every single qualification. We are dedicated to building a diverse, inclusive, and authentic workplace that is free from discrimination and harassment; this allows us to make better decisions and better serve the communities we’re a part of. So if you're excited about this role but your previous experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

All applicants receive consideration for employment. We do not discriminate on the basis of race, religion, color, national origin, gender identity, sexual orientation, pregnancy, age, marital status, veteran status, or disability status. 

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