Senior Data Engineer

About the Role

We are seeking a Senior Data Engineer to architect, build, and own a complete data ecosystem in a fast-growing, cloud-native environment. This role offers the rare opportunity to design and implement data infrastructure from the ground up, with a focus on AWS technologies such as Redshift, DynamoDB, and RDS. You’ll also develop reverse ETL pipelines to operationalize insights across core systems, helping shape how data drives decision-making company-wide.

You will work remotely from Poland, collaborating cross-functionally with product, engineering, and growth teams. Your work will directly influence company strategy and empower every team to make informed, data-driven decisions.
 

Key Responsibilities
 

Data Ownership and Architecture

• Serve as the primary data engineer responsible for designing and maintaining the company’s end-to-end data infrastructure.
• Define and implement scalable, high-performance data systems capable of supporting millions of users.
• Make architectural decisions that set the foundation for long-term data strategy.
   

AWS Data Infrastructure

• Design and optimize AWS Redshift as the central analytics warehouse.
• Build ingestion pipelines from RDS, DynamoDB, and other NoSQL sources.
• Leverage AWS services (Lambda, Glue, Kinesis, S3) for a modern and efficient data stack.
• Manage query performance tuning, cluster scaling, and cost optimization.
   

Reverse ETL and Data Activation

• Build reverse ETL pipelines to operationalize analytics data.
• Sync enriched datasets to production systems, CRM, and customer engagement tools.
• Implement real-time data activation and feedback loops that improve user experience.
   

Scalability and Governance

• Rapidly prototype and deploy data solutions to support business growth.
• Develop self-service analytics capabilities for non-technical teams.
• Establish and maintain scalable data governance and data quality frameworks.
   

Technical Leadership

• Define and enforce best practices in data engineering and cloud infrastructure.
• Mentor engineers on AWS and data technologies.
• Translate complex business needs into technical solutions.
• Champion data quality, consistency, and reliability across all systems.
   

Requirements

• 5+ years of hands-on experience with AWS Redshift, including performance tuning and cluster management.
• 3+ years working with AWS RDS and DynamoDB, including NoSQL modeling.
• Proven experience implementing reverse ETL pipelines and data activation frameworks.
• Strong programming skills in Python or equivalent language for data pipelines.
• Experience independently leading data infrastructure projects or serving as a solo data engineer.
• Strong knowledge of modern data stack tools (e.g., dbt, Airflow, Fivetran, Census).
• Familiarity with streaming architectures, real-time analytics, and data warehousing principles.
• Proficiency with Infrastructure as Code (Terraform preferred).
• Excellent communication skills and ability to work effectively in remote, distributed teams.
• Experience working in SaaS or scale-up environments, including familiarity with SaaS metrics and data challenges.
   

Technical Competencies

• Advanced SQL and query optimization.
• Experience with CDC (Change Data Capture) and API-based data services.
• Knowledge of data quality frameworks and metadata management.
• Cost optimization for AWS data workloads.
• Understanding of SaaS data models, including multi-tenancy and subscription analytics.
   

Preferred Qualifications

• Experience with AWS Kinesis or other real-time streaming platforms.
• Exposure to ML pipelines or AWS SageMaker.
• Familiarity with customer data platforms (CDPs).
• Experience in product analytics and experimentation systems.
• Contributions to open-source data tools or frameworks.