Staff Data EngineerDeepL

As a Senior Staff Data Engineer, you'll be a strategic technical leader within our Data Track and beyond driving the evolution of our enterprise-wide data practices. You'll work at the intersection of data engineering, product facing teams and platform teams, establishing standards and best practices that enable our engineering teams to deliver reliable, scalable, and secure data solutions. This role requires both deep technical expertise and the ability to influence and mentor engineers across DeepL. Your responsibilities Strategic Leadership & Architecture

• Define and implement enterprise-wide Data engineering standards, strategies, and best practices for data solutions
• Provide expert guidance on technology selection, cloud services (AWS), and architectural decisions for data solutions
• Drive continuous improvements in efficiency, cost reduction, and innovation across data
• Evaluate and recommend tools, technologies, and frameworks to enhance our data capabilities

Collaboration & Mentorship

• Partner with and influence leaders from engineering, analytics, machine learning, and security teams to align on goals
• Mentor and be a thought leader across data, engineering and platform teams, fostering a culture of technical excellence
• Collaborate with cross-functional stakeholders to understand data requirements and translate them into technical solutions
• Work closely with customer-facing teams to ensure data solutions meet enterprise client needs

Security, Governance & Compliance

• Drive best practices in data security, governance, and compliance aligned with enterprise B2B standards
• Implement robust security measures for data at rest and in transit
• Ensure thorough documentation of data processes, systems architecture, and stakeholder dependencies
• Maintain compliance with GDPR, SOC 2, and other relevant regulatory requirements

• Extensive Data expertise: 10+ years of experience in data engineering or related role with at least 5 years in a staff or principal role
• Data architecture experience: Deep understanding of data infrastructure, data warehousing, ETL/ELT processes, and/or data pipeline orchestration
• Cloud mastery: Proven experience with cloud platforms (AWS, Azure, or GCP) and cloud-native data services
• Scripting & automation: Advanced scripting skills in Python, Bash, or similar languages for automation and tooling
• Leadership & communication: Proven track record of technical leadership, mentoring engineers, and influencing cross-functional teams
• Enterprise experience: Experience working in high-growth technology or SaaS environments with distributed systems and microservices architecture
• Experience with data-specific tools and technologies such as Apache Airflow, dbt, Apache Spark, Kafka, or similar
• Experience with real-time streaming data processing pipelines (spark, flink, etc.)
• Knowledge of data warehousing solutions (Snowflake, BigQuery, Redshift) and data lake architectures
• Background in data engineering or analytics engineering

Nice to haves

• Familiarity with machine learning operations (MLOps) and ML infrastructure
• Experience with security best practices, including secrets management, network security, and compliance frameworks
• Experience with agile methodologies and tools (Jira, Confluence) for managing project timelines and deliverables
• Contributions to open-source projects or technical community involvement
• Experience with cost optimization strategies for cloud infrastructure

Helping people overcome communication barriers is the heart of what we do. Founded in Germany in 2017 by a team of engineers and researchers, DeepL has developed the world’s most accurate AI translation technology—enabling real-time, human-sounding translation.

Accessible via a web translator, browser extensions, desktop and mobile apps, and an API, DeepL supports a best-in-class translation experience in 34 languages and counting. Our 550-person team operates across four European hubs in Germany, the Netherlands, the UK, and Poland.