Senior Data Engineer

Summary

Join Twilio as a Senior Data Engineer to contribute to the development of Marketing Data Science and GenAI capabilities. Collaborate with data scientists and analysts to support analytics across B2B and B2C funnels, enabling developers and identifying opportunities for sales teams. Design, build, deploy, and maintain the technology architecture for data capture, management, storage, and utilization. Work with a visible Analytics team advising the CMO on growth and forensics. This role offers broad collaboration across multiple teams and a chance to make a significant impact. The position requires strong data engineering and analytics skills, proficiency in programming languages, and experience with cloud platforms and data warehousing technologies. The role is remote, based in Ontario, with approximately 10% anticipated travel.

Requirements

• 5+ years with fluency in Data Engineering and analytics tools (Airflow, Spark)
• Proficiency in programming languages such as Python, SQL, and/or Scala
• Experience with cloud platforms such as AWS, GCP is a plus
• Experience with data warehousing technologies (e.g., Snowflake, Redshift, BigQuery)
• Strong proficiency in data modeling, ETL development, and data integration
• Knowledge of data governance principles, data security, and compliance
• Strong communication and collaboration skills
• Excellent problem-solving skills and attention to detail

Responsibilities

• Integrate data from multiple sources including databases, APIs, logs, and third-party systems, ensuring data quality and consistency
• Design, develop, and optimize Extract, Transform, Load (ETL) processes to move and transform data from source systems to target systems efficiently
• Implement and maintain data warehouses or data lakes, optimizing for storage, querying performance, and accessibility for analytics and reporting
• Establish and enforce data governance policies and best practices to ensure data security, privacy, quality, and compliance with regulatory requirements
• Monitor and optimize the performance of data pipelines, databases, and data processing frameworks to meet SLAs and handle growing data volumes
• Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand requirements and deliver solutions
• Document data engineering processes, architectures, and best practices
• Troubleshoot data-related issues, providing timely resolution and support to maintain data availability and reliability
• Implement automation and orchestration tools to streamline data engineering workflows, reduce manual intervention, and improve efficiency
• Manage data engineering projects from inception to delivery, including scoping, resource allocation, scheduling, and tracking progress against milestones and deliverables

Preferred Qualifications

Bachelor's degree in Computer Science, Engineering, or related field; Master's degree preferred

Benefits

• Competitive pay
• Generous time off
• Ample parental and wellness leave
• Healthcare
• A retirement savings program