What you will do
- Design, develop, and maintain scalable ETL/ELT pipelines and data workflows.
- Optimize data storage, processing, and retrieval using cloud-based technologies, with a strong focus on AWS.
- Work with structured and unstructured data across various databases and data lakes.
- Ensure data integrity, security, and compliance with industry standards.
- Collaborate with cross-functional teams to define data requirements and support analytics and machine learning initiatives.
- Monitor and improve data infrastructure performance, ensuring reliability and scalability.
- Implement best practices for data governance, quality, and observability.
- Develop and maintain robust data injection processes to ensure seamless data flow across systems.
- Design and optimize data models to support analytical and operational use cases.
What should your qualifications be
- 5+ years of experience in data engineering or a related field.
- Strong expertise in AWS data services (e.g., Redshift, Glue, Athena, S3, Lambda, Kinesis, etc.).
- Experience with big data technologies such as Apache Spark, Apache Airflow, or similar tools.
- Strong knowledge of SQL and data modeling, schema design.
- Strong hands-on experience in Python
- Knowledge of CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation) is a plus.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication skills and ability to collaborate with technical and non-technical stakeholders.
- Fluent English (B2) with both written and spoken skills used for clear and active communication with native speakers
- Experience with real-time data streaming and event-driven architectures.
- Exposure to machine learning workflows and MLOps practices.
- Knowledge of security and compliance standards in data engineering.
- Experience with GCP or Azure is a plus (BigQuery, Databricks, Azure Data Factory, etc.)
Benefits
- Compensation Package
- Vacation leave of 20 working days
- 4 sick days per year
- Personal Growth
- Career and professional growth
- Access to senior engineers for help and mentorship
- English classes with on-staff teachers
- English clubs where you can polish your skills together with teammates
- Other Perks
- Possibility for working remote or in coworking space
- Macbook provided by company as a working environment
- Work environment based on collaboration and teams
- Team building events on team and group level
- Sponsored company outings and social events
Skills Required
- 5+ years of experience in data engineering or a related field.
- Strong expertise in AWS data services, including Redshift, Glue, Athena, S3, Lambda, and Kinesis.
- Experience with big data technologies such as Apache Spark, Apache Airflow, or similar tools.
- Strong knowledge of SQL, data modeling, and schema design.
- Strong hands-on experience with Python.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication skills and ability to collaborate with technical and non-technical stakeholders.
- Fluent English at B2 level, written and spoken.
- Knowledge of CI/CD pipelines and infrastructure as code using Terraform or CloudFormation.
- Experience with real-time data streaming and event-driven architectures.
- Exposure to machine learning workflows and MLOps practices.
- Knowledge of security and compliance standards in data engineering.
- Experience with GCP or Azure, including BigQuery, Databricks, or Azure Data Factory.
What We Do
Remedy Product Studio works with founders on strategy, execution, and launch of digital products. We collaborate with Seed to Series C companies across healthcare, data, and finance/commerce technology. We have been a long-term partner to companies including ClassPass, HealthReveal, H1 Insights, Sommsation, Ash, and Caraway Health. Partners are typically with us for 3 years, and we engage our venture network to guide them through an average of 2 fundraises, helping them secure investors like Google Ventures, Greycroft, and Serena Ventures. We work closely with investors to fill out rounds and invest in select partners in the form of sweat equity. So, what does a Remedy partnership look like? - Each Remedy team works exclusively with a single partner to synthesize company objectives, create a roadmap, and then deliver a product. - With our unique flavor of agile methodology, our product-led teams distill a partner’s broad vision into a lean scope that can be delivered and tested in a short time frame. - Our cross-functional teams work on product management, full stack and data engineering, DevOps, architecture, QA, and UX/UI design. Throughout a partnership, we gather product metrics to inform long-term technology and business strategy.
