We are seeking a skilled and dedicated Data Engineer to join our dynamic team. As a Data Engineer, you will play a pivotal role in building and maintaining our data infrastructure and pipelines, enabling seamless data integration, analysis, and reporting. This is an exciting opportunity to join a rapidly growing team and make a significant impact on our data-driven product development and business strategy.
🛠 You will
- Design, develop, and optimize scalable data pipelines and workflows to support the collection, storage, processing, and analysis of large volumes of data.
- Design, build, and operate core infrastructure (e.g., APIs, services and frameworks) and tooling used by all of Stripe’s engineering teams, for example to annotate and automatically de-identify sensitive data
- Implement data models and database schemas to facilitate effective data storage and retrieval.
- Monitor and troubleshoot data pipelines, ensuring data quality, reliability, and performance.
- Identify and implement strategies for data governance, security, and privacy.
- Stay up to date with industry trends and best practices in data engineering and recommend relevant technologies and tools to enhance our data infrastructure.
- Help the Data Science team apply and generalize statistical models on large datasets
🙌 Your profile
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer or in a similar role, ideally within a fast-paced startup environment.
- Strong programming skills in languages such as Python, Java, or Scala.
- Proficiency in working with big data processing frameworks and distributed computing technologies.
- Solid understanding of relational and NoSQL databases, data modeling, and SQL.
- Experience with data integration and ETL tools.
- Solid experience with streaming and high performance data processing technologies and frameworks
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and their data services.
- Excellent problem-solving skills and ability to work independently in a dynamic environment.
- Strong communication and collaboration skills to work effectively with cross-functional teams.
💯 Preferred Qualifications
- Experience in MLOps and building tooling for data scientists, enabling efficient model deployment and monitoring.
- Experience with cloud-based data warehousing solutions like Amazon Redshift or similar platforms, enabling scalable and performant data storage and retrieval.
- Knowledge of data exploration and visualization tools such as Looker, facilitating intuitive and actionable insights for stakeholders.
- Confidence in utilizing platforms like Databricks for efficient big data processing and analytics.
- Strong familiarity with version control systems and best practices for collaborative software development.
- Previous exposure to machine learning concepts, frameworks, and model deployment processes.
- Experience in working within Agile development methodologies, promoting iterative and efficient project delivery.
🤗 Benefits
- Do something meaningful; help stop human trafficking, money laundering, child labor; be a part of enabling the future of how money moves.
- Work alongside a highly competent, top-tier team (Y Combinator, ex AWS, Zalando, Palantir).
- Great career development opportunities in a fast-growing early-stage startup.
- Low-bureaucracy, minimal meetings, async communications culture, international culture, flat organization.
- We do not recommend you apply if you aren't confident in delivering results. We maintain an extremely high bar for all of our team members. We do performance evaluations honestly & fairly, not kindly.
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