Designs, builds, and maintains scalable ETL/ELT pipelines, data models, storage solutions, and data workflows, primarily using AWS. Ensures data integrity, governance, security, observability, reliability, and performance across structured and unstructured data systems. Collaborates with product, engineering, analytics, and machine learning teams to support data-driven initiatives and optimize analytical and operational data infrastructure.
Who we are
Product Strategy. Technology Execution. Launch. Investment.
Remedy Product Studio is a rapidly scaling technology company specializing in working with and investing in prominent start-ups and brands in building and scaling their digital products. We use data-driven agile approaches coupled with high performing teams as a cornerstone of our technology-first culture.
We partner with startups to strategize, execute, launch, and invest in digital products, including web apps, mobile apps, data science tools, and firmware for connected devices.
We believe that people make a great company, and that's why we want you to join us!!!
Who we're looking for
As a Senior Data Engineer, you will be responsible for designing, implementing, and maintaining scalable data pipelines and storage solutions. You will work closely with product managers, engineers, and analysts to ensure efficient data workflows and enable data-driven decision-making. The ideal candidate has a strong background in data engineering, with expertise in AWS and a familiarity with GCP or Azure as a plus.
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.)
Nice to Have:
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
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