Role Overview
As a Senior Data Engineer, you will play a central role in shaping and maintaining customer-facing data systems within a high-performance environment. You'll work directly with modern AWS technologies to handle thousands of events per second and manage rapidly expanding data volumes. This is a hands-on position focused on building, optimizing, and operating data infrastructure that powers core product capabilities.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using AWS services such as S3, Kinesis, Lambda, and Athena.
- Partner with product and technical stakeholders to define and execute the data product roadmap.
- Build reusable frameworks for ingesting, transforming, and monitoring large-scale datasets.
- Lead architectural decisions for data platforms, ensuring scalability, reliability, and performance.
- Implement and operate data processing systems using Spark, Airflow, and dbt.
- Champion data quality, observability, and pipeline reliability through automation, testing, and CI/CD practices.
- Promote engineering best practices across the team, including version control, security, and infrastructure as code.
What We’re Looking For
- Minimum of 5 years in data engineering roles with a focus on cloud-based data platforms.
- Proven experience with data warehousing and data lake architectures.
- Strong proficiency in Python and SQL, with experience in building automated data workflows.
- Familiarity with AWS cloud services such as EMR, Glue, EC2, and S3.
- Hands-on experience with data orchestration tools, particularly Airflow.
- Solid understanding of relational database design and cloud data warehouses like Snowflake or Redshift.
- Experience with Spark, Pandas, or similar data processing frameworks.
Nice to Have
- Production experience managing petabyte-scale datasets.
- Exposure to Infrastructure as Code tools like Terraform or CloudFormation.
- Familiarity with analytics and BI platforms such as Tableau, Looker, or Power BI.
- Curiosity about emerging data technologies including Apache Iceberg, Dagster, and Great Expectations.
- Basic understanding of machine learning concepts such as supervised learning, overfitting, and cross-validation, as well as LLM-related techniques like fine-tuning.
Work Environment & Culture
This role operates in a hybrid model with locations in Zielona Góra and Wrocław, offering flexibility to work remotely with company-provided equipment or on-site. The team values autonomy, evidence-based decision-making, and open communication. You'll join a diverse, multilingual environment where innovation is encouraged and different perspectives are welcomed.
Engineering decisions are driven by data, not hierarchy. Teams are empowered to own their roadmaps and deliver impactful solutions. The culture balances focused work with team engagement, supported by regular events and opportunities for personal development.
Compensation & Benefits
- Annual salary reviews based on individual performance and company outcomes.
- Referral bonuses ranging from 4,000 to 20,000 PLN depending on role complexity.
- Personal training budget of up to 7,000 PLN per year for certifications, conferences, and learning platforms.
- Matching contributions up to 500 PLN annually for charitable donations.
- Free private medical insurance and attractive life insurance coverage.
- Support for wellness, including gym membership co-financing and sports activity subsidies.
- Flexible vacation policy with up to 30 days off per year, increasing with tenure.
- Weekly language classes in English, Spanish, and German.
- Employee Assistance Program offering free psychological support.
- One paid day off per year for volunteering.
- Access to online learning platforms such as LinkedIn Learning.
- Company-provided equipment for remote work and modern office spaces with complimentary snacks and beverages.
