Data Engineer, Speak

• Data Modeling: Deep understanding of data structures, theories, principles, and practices. Ability to design, implement, and manage data warehouses effectively
• Big Data Technologies: Proficiency in big data technologies and frameworks such as DBT, Airflow, etc., to handle large-scale data processing and analysis
• Programming Skills: Strong programming skills in languages relevant to data engineering (Python and SQL). Ability to write efficient, reliable, and maintainable code
• Data Pipeline and ETL Development: Experience in building and optimizing data pipelines, architectures, and data sets. Familiarity with ETL (extract, transform, load) processes and tools
• Cloud Computing: Knowledge of cloud services (GCP BigQuery, dbt) and understanding of how to leverage them for data processing and storage solutions
• Data Analysis and Visualization: Ability to analyze data to identify patterns, anomalies, and insights. Proficiency in using data visualization tools(eg Mode) to communicate findings clearly
• Debugging Skills: Strong problem-solving skills and the ability to approach complex challenges methodically including data inconsistency issues
• Effective Communication: Ability to communicate technical information to non-technical stakeholders clearly and effectively. This includes writing documentation, presenting findings, and collaborating on projects

Desirable

• As an Data Engineer at Speak, you'll play a pivotal role in shaping the future of digital language learning, propelling us towards our mission of making language proficiency accessible to millions worldwide
• Your responsibilities will span the crucial intersection of data infrastructure and analytics, from managing scalable data pipelines that support real-time processing, to deploying sophisticated analytics solutions that drive personalized learning experiences
• You'll work closely with our product, engineering, and data science teams to ensure that our platform, powered by cutting-edge technology, is not only robust but also delivers actionable insights that enhance user engagement and learning outcomes
• Design and Build Data Infrastructure: You'll architect and implement robust, scalable data pipelines that ensure efficient data flow and processing, supporting both real-time analytics and large-scale, batch processing needs. Your work will be critical in managing the ingestion, storage, and accessibility of data from various sources, ensuring our platform's backbone is strong and reliable
• Enable Data-Driven Decisions: By collaborating with cross-functional teams, you will develop and deploy tools and frameworks that facilitate data access and analysis, empowering product and business teams to make informed decisions. This includes creating dashboards, reports, and advanced analytics models that reveal user behavior patterns, learning efficacy, and opportunities for product improvement
• Optimize Data Architecture: Constantly evaluate and refine the data architecture to support our growing data needs and ensure optimal performance. This includes managing data lakes, data warehouses, and databases, as well as implementing best practices for data modeling, data quality, and data governance
• Support Machine Learning Projects: Work closely with data scientists and machine learning engineers by providing them with clean, structured data for building and deploying predictive models that enhance personalized learning experiences and engagement strategies
• Innovate and Experiment: Stay ahead of the curve by researching and implementing cutting-edge technologies and methodologies in data engineering and analytics
• Collaborate Across Teams: As a key player in the engineering team, you'll work closely with product managers, analysts, and other engineers to bring data-driven products and features from concept to launch