Data Engineer
| Company | Speak |
|---|---|
| Location | San Francisco, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Mid Level |
Requirements
- Deep understanding of big data warehouses (BigQuery, Snowflake, Redshift), theories, principles, and practices. Ability to design, implement, and manage data warehouses effectively.
- Strong programming skills in Python and SQL. Ability to write efficient, reliable, and maintainable code.
- Experience in building and optimizing data pipelines, architectures, and datasets. Familiarity with ETL (extract, transform, load) processes and tools.
- Experience with end-to-end data platform beyond creating pipelines, such as data ingestion, reverse ETL, visualization, data observability, etc.
- Knowledge of cloud services (GCP, AWS, dbt) and understanding of how to leverage them for data processing and storage solutions.
- Ability to analyze data to identify patterns, anomalies, and insights. Proficiency in using data visualization tools (e.g. Mode) to communicate findings clearly.
- Strong problem-solving skills and the ability to approach complex challenges methodically including data inconsistency issues.
- Ability to communicate technical information to non-technical stakeholders clearly and effectively. This includes writing documentation, presenting findings, and collaborating on projects.
Responsibilities
- You’ll architect and implement robust, scalable data pipelines using Airflow for orchestration and dbt for transformation that ensure efficient data flow and processing.
- 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.
- Constantly evaluate and refine the data architecture to support our growing data needs and ensure optimal performance.
- Work closely with analysts 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.
- Stay ahead of the curve by researching and implementing cutting-edge technologies and methodologies in data engineering and analytics.
- 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.
Preferred Qualifications
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No preferred qualifications provided.