Spontaneous Application - Data Engineer

Accountabilities

• Design, build, and maintain scalable data pipelines for collecting, storing, transforming, and processing data from multiple sources.


• Develop and maintain robust data models and schemas that support analytics, reporting, machine learning, and product development.


• Create, maintain, and optimize ETL processes that extract, transform, and load data into cloud-based data warehouses.


• Work closely with ML engineers, data analysts, software developers, product teams, and other stakeholders to understand data requirements and deliver appropriate technical solutions.


• Monitor data pipelines and processes to maintain high standards of data quality, reliability, availability, and performance.


• Identify bottlenecks and optimize data infrastructure and processing workflows as data volumes and product requirements grow.


• Contribute to the design of the broader data architecture, ensuring that pipeline components and cloud infrastructure work together effectively.


• Help establish reliable and accessible data foundations that enable data-driven business decisions and machine learning models.


• Participate in solving complex engineering challenges across data processing, infrastructure, and large-scale data systems.


• Contribute ideas and technical expertise to improve data capabilities and support ongoing product innovation.

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical discipline.


• At least 3 years of professional experience as a Data Engineer or in a comparable data-focused engineering role.


• Strong programming skills in Python, Java, or a similar programming language.


• Solid knowledge of SQL and data modeling principles.


• Professional experience with cloud-based data warehousing technologies such as Amazon Redshift, Google BigQuery, or equivalent platforms.


• Experience with data processing and ETL technologies such as Spark, Flink, Databricks, Snowflake, or similar tools.


• Familiarity with messaging and event-streaming systems such as Kafka, RabbitMQ, or equivalent technologies.


• Good understanding of cloud infrastructure and how different components of a modern data pipeline interact.


• Strong analytical and problem-solving abilities, with the capacity to investigate complex technical issues and develop scalable solutions.


• Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.


• Comfortable working in a fast-paced, evolving environment where ownership and initiative are highly valued.


• Ability to work from a location within approximately the GMT-3 to GMT+2 time zones.

• Competitive salary.


• Health insurance.


• Stock options.


• Remote working environment.


• Opportunity to work within a highly technical and engineering-focused team.


• Exposure to challenging data, machine learning, infrastructure, and product engineering problems.


• Strong opportunities for professional growth and learning within a rapidly scaling technology company.


• Collaborative work environment with strong team spirit and a high degree of technical ownership.


• Annual company trip to a secret destination.


• Opportunity to contribute to innovative, data-driven products with meaningful customer impact.

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