Senior Data Engineer

Accountabilities

• Design, build, and maintain scalable data pipelines from source systems through data warehouses and analytics platforms.
• Create and optimize data ingestion workflows using cloud-native technologies, orchestration tools, and Python-based data loaders.
• Create and maintain reliable data models that enable accurate reporting, business intelligence, and self-service analytics.
• Deliver actionable analyses that explain business performance and support strategic decision-making.
• Build data infrastructure with scalability, reliability, performance, and cost optimization as core design principles.
• Manage infrastructure as code to ensure consistent, automated deployment and maintenance of the data platform.
• Partner closely with product, finance, growth, and engineering teams to translate business questions into trusted data solutions.
• Leverage AI-powered development tools to improve engineering productivity while maintaining full ownership of production quality.
• Maintain monitoring, troubleshooting, and continuously improving data pipelines and platform performance.
• Stay current with emerging technologies and best practices in data engineering, cloud infrastructure, and artificial intelligence.

Requirements

• 5+ years of experience designing, building, and operating production-grade data pipelines and modern data platforms.
• Strong expertise with cloud data technologies such as Google Cloud Platform, BigQuery, dbt, Airflow, Dataflow, or equivalent solutions.
• Experience with infrastructure as code using tools such as Pulumi or Terraform.
• Advanced SQL skills and proficiency in Python for data engineering and automation.
• Experience working with analytics platforms and transforming complex datasets into business insights.
• Familiarity with AI-assisted development tools and an understanding of how to apply them responsibly within engineering workflows.
• Strong analytical thinking with the ability to identify root causes behind business metrics and performance changes.
• Excellent communication skills with the ability to collaborate effectively across technical and non-technical teams.
• Comfortable working independently in a fast-paced, remote-first environment with a high level of ownership.
• Passion for scalable data engineering, continuous learning, and building reliable systems that support business growth.

Benefits

• Full-time remote position with flexible work schedule.
• Equity participation through an employee stock ownership program (ESOP).
• Technology allowance for home office setup.
• Comprehensive health insurance, including full employee coverage and substantial dependent coverage.
• Annual professional development budget.
• Annual company off-site events.
• Opportunity to work with modern cloud technologies, large-scale data systems, and cutting-edge AI tools.
• Collaborative, international environment focused on innovation, ownership, and continuous growth.

Schedule

• Full-time remote position.

Pay

• Competitive salary based on experience and qualifications.

Qualifications

• Master’s degree in Computer Science, Engineering, Statistics, or related field.
• Proven track record of delivering high-quality data engineering projects.
• Experience with distributed systems, microservices, and containerization.
• Knowledge of data warehousing, ETL processes, and data governance principles.
• Experience with NoSQL databases and distributed storage systems.
• Experience with data visualization tools and platforms.
• Experience with cloud-native architectures and tools.
• Experience with machine learning and AI techniques.

Skills

• Data engineering
• Data modeling
• Data warehousing
• Data analysis
• Cloud computing
• Python programming
• SQL
• AI/ML

Benefits

• Flexible work schedule
• Equity participation
• Technology allowance
• Health insurance
• Professional development budget
• Company off-site events
• Modern cloud technologies
• Collaborative environment