Software Engineer, Data Platform at Grammarly

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 25

Salary

0.0

Posted On

23 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Data Engineering, Data Modeling, SQL, Spark, Kafka, Terraform, Python, Scala, Java, ETL, ELT, Airflow, Data Governance, Data Privacy, Cloud Infrastructure, Data Lakes, Machine Learning

Industry

Software Development

Description

Grammarly offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture. About Grammarly Grammarly is the trusted AI assistant for communication and productivity, helping over 40 million people and 50,000 organizations do their best work. Companies like Atlassian, Databricks, and Zoom rely on Grammarly to brainstorm, compose, and enhance communication that moves work forward. Grammarly works where you work, integrating seamlessly with over 500,000 applications and websites. Founded in 2009, Grammarly is No. 7 on the Forbes Cloud 100, one of TIME’s 100 Most Influential Companies, one of Fast Company’s Most Innovative Companies in AI, and one of Inc.’s Best Workplaces. The Opportunity To achieve our ambitious goals, we’re looking for a Software Engineer to join our Data Platform team and help us build a world-class data platform. Grammarly’s success depends on its ability to efficiently ingest over 60 to 70 billion daily events while using our systems to improve our product. This role presents a unique opportunity to experience all aspects of building complex software systems, including contributing to the strategy, defining the architecture, and developing and shipping to production. 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 a Software Engineer on the Data Platform team, you will shape the architecture and technical strategy of our data platform, ensuring scalability, security, and efficiency across data engineering systems. You will design and lead the implementation of robust, scalable, and reliable systems that handle large volumes of data, empowering both product features and data-driven decision-making across the company. Your work will span areas such as real-time & ETL data pipelines, cloud infrastructure, data lakes, and back-end services. This role requires you to collaborate with cross-functional teams, including back-end engineers, Analytics engineering, Data Science engineering, and machine learning teams, to drive initiatives that support various business outcomes. As a senior IC, you will also mentor engineers and help set the strategic direction for the platform. In this role, you will: Architect and lead the development of large-scale systems for data pipelines, data lakes that handle billions of daily events. Design and implement solutions that ensure data is available, secure, and scalable across the platform, enabling real-time and batch processing. Make high-level architectural decisions about system design, technology choices, and platform evolution, ensuring scalability and long-term sustainability. Collaborate with key stakeholders, such as product teams, data engineers, back-end developers, and ML engineers, to build tools & frameworks that power analytics, product features, and data-driven workflows. Work with business stakeholders such as Analytics Eng, Data Science, Machine Learning, and Produce teams to build high-impact data products enabling business-critical features, research, and experimentation with a focus on efficiency and alignment Collaborate with Leadership in devising the charter and technical roadmaps Mentor engineers across back-end infrastructure and data engineering disciplines, fostering a culture of collaboration and technical excellence. Qualifications Has experience in large-scale distributed computing systems, with expertise in both data engineering and data modeling. Has experience managing live production environments, including high-load systems or data-intensive workflows, with a focus on uptime and reliability. Expert in SQL and proficient in technologies like Spark, Kafka, Terraform, and in at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java). Strong knowledge of ETL/ELT design patterns, orchestration tools (e.g., Airflow, dbt, Dagster), and data quality frameworks. Ability to design scalable, secure, and maintainable data models and architectures, and understanding of data governance, privacy regulations (GDPR/CCPA). Hands-on experience with modern data storage technologies (e.g., Delta Lake, Snowflake, BigQuery, Redshift). Is a strategic thinker, able to evaluate whether to build internally or leverage third-party solutions, ensuring the right balance between speed, scalability, and long-term viability. Is an excellent communicator and collaborator, able to work across diverse teams and stakeholders, translates business needs into robust data solutions, and ensures alignment on technical goals. Has a demonstrated ability to work independently with minimal to zero guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments. Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable. Is inspired by our MOVE principles: move fast and learn faster; obsess about creating customer value; value impact over activity; and embrace healthy disagreement rooted in trust. Support for you, professionally and personally Professional growth: We hire people we trust, and we give team members autonomy to do their best work. We also support professional development 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. We have a highly collaborative culture supported by our EAGER values. We also take time to celebrate our colleagues and accomplishments with global, local, and team-specific events and programs. Comprehensive benefits: Grammarly offers all team members competitive pay along with a benefits package that includes superior health care. We also offer ample and defined time off, catered lunches, gym and recreation stipends, admission discounts, and more. Relocation Support: Grammarly provides comprehensive relocation support to make your move to Berlin seamless. Our package includes visa assistance, destination services to help you and your family settle in comfortably, and a relocation bonus to cover additional expenses, such as temporary housing. We encourage you to apply At Grammarly, we value our differences, and we encourage all—especially those whose identities are traditionally underrepresented in tech organizations—to apply. Grammarly is an equal opportunity company. We do not discriminate on the basis of race or ethnic origin, religion or belief, color, gender expression or identity, sexual orientation, sexual identity, national origin, citizenship, age, marital status, veteran status, disability status, criminal prosecution, judgment in a criminal case, or any other characteristic protected by law. 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. #LI-Hybrid

Responsibilities

As a Software Engineer on the Data Platform team, you will shape the architecture and technical strategy of our data platform, ensuring scalability, security, and efficiency across data engineering systems. You will design and lead the implementation of robust, scalable, and reliable systems that handle large volumes of data, empowering both product features and data-driven decision-making across the company.