Senior Analytics Engineer

Grammarly is excited to offer a remote-first hybrid working model. Team members work primarily remotely in the United States, Canada, Ukraine, Germany, or Poland. Certain roles have specific location requirements to facilitate collaboration at a particular Grammarly hub.

All roles have an in-person component: Conditions permitting, teams meet 2–4 weeks every quarter at one of Grammarly’s hubs in San Francisco, Kyiv, New York, Vancouver, and Berlin, or in a workspace in Kraków. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that fosters trust and unlocks creativity.

Grammarly team members in this role must be based in Germany or Poland, and they must be able to collaborate in person 3 weeks per quarter, traveling, if necessary, to the hub(s) where the team is based.

The opportunity 

Grammarly is the world’s leading AI writing assistance company trusted by over 30 million people and 70,000 professional teams every day. From instantly creating a first draft to perfecting every message, Grammarly’s product offerings help people at 96% of the Fortune 500 get their point across—and get results. Grammarly has been profitable for over a decade because we’ve stayed true to our values and built an enterprise-grade product that’s secure, reliable, and helps people do their best work—without selling their data. We’re proud to be one of Inc.’s best workplaces, a Glassdoor Best Place to Work, one of TIME’s 100 Most Influential Companies, and one of Fast Company’s Most Innovative Companies in AI.

To achieve our ambitious goals, we’re looking for an Analytics Engineer to enable Grammarly to make better, faster, data-driven business decision-making. As part of our esteemed data team, this role is pivotal in allowing us to make quicker, more informed business decisions. The person in this role will have the opportunity to help build an exceptional Analytics stack, foster a data-driven culture throughout our organization, and empower decision-makers at all levels with a reliable source of truth.

The Analytics Engineer will team up with product, marketing, and business leaders, alongside other data experts, to create exceptional and scalable analytical solutions for our company.

Grammarly’s engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.

Your impact

As an Analytics Engineer, you will:

• Own the last mile data delivery for product and business stakeholders.
• Form a deep understanding of the business, your partners’ opportunities and problems, and how they can be solved using data.
• Work closely with data scientists to define and operationalize critical business metrics.
• Team with data engineers to design dimensional tables to be used by power users and other developers.
• Write complex, production-grade SQL pipelines using engineering best practices for testing, version control, and documentation.
• Create scalable analytical solutions such as dashboards, alerts, and tools to enable self-serve reporting and analysis capabilities of your users.
• Continuously re-evaluate our data ecosystem against industry best practices and new 3rd party technologies to ensure Grammarly’s analytics stack remains best-in-class.

We’re looking for someone who

• Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
• Is inspired by our MOVE principles, which are the blueprint for how things get done at Grammarly: move fast and learn faster, obsess about creating customer value, value impact over activity, and embrace healthy disagreement rooted in trust.
• Is able to collaborate in person 3 weeks per quarter, traveling if necessary to the hub where the team is based.
• Is excellent at using SQL for data pipeline development in a modern data stack (Databricks, Snowflake, BigQuery, Redshift, dbt etc.)
• Has 8+ years of work experience as an Analytics Engineer, Data Engineer, Business Intelligence Engineer, Product Analyst, or a similar role.
• Is familiar with data modeling principles and best practices.
• Has strong analytical and critical thinking skills, high attention to detail, and a strong bias toward impact and actionable insights.
• Has a passion for communicating insights through the language of data.

Support for you, professionally and personally

• Professional growth: We believe that autonomy and trust are key to empowering our team members to do their best, most innovative work in a way that aligns with their interests, talents, and well-being. We also support professional development and advancement with training, coaching, and regular feedback.
• A connected team: Grammarly builds a product that helps people connect, and we apply this mindset to our own team. Our remote-first hybrid model enables a highly collaborative culture supported by our EAGER (ethical, adaptable, gritty, empathetic, and remarkable) values. We work to foster belonging among team members in a variety of ways. This includes our employee resource groups, Grammarly Circles, which promote connection among those with shared identities including BIPOC and LGBTQIA+ team members, women, and parents. We also celebrate our colleagues and accomplishments with global, local, and team-specific programs. 

We encourage you to apply

At Grammarly, we value our differences, and we encourage all to apply. Grammarly is an equal opportunity company. We do not discriminate on the basis of race or ethnic origin, religion or belief, gender, disability, sexual identity, or age.

For more details about the personal data Grammarly collects during the recruitment process, for what purposes, and how you can address your rights, please see the Grammarly Data Privacy Notice for Candidates here. 

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All team members meeting in person for official Grammarly business or working from a hub location are strongly encouraged to be vaccinated against COVID-19.