You will lead the development and maintenance of scalable data architectures that power customer-facing data products. Working within a flat, evidence-driven engineering culture, you'll design and operate data pipelines using modern AWS tools, ensuring reliability, observability, and performance at scale.
What You'll Do
- Design, build, and manage data pipelines and analytics systems using AWS technologies including S3, Athena, Lambda, and Kinesis.
- Collaborate with product and technical stakeholders to shape the strategy and implementation of data products.
- Develop scalable frameworks for data ingestion, transformation, monitoring, and value extraction from large datasets.
- Lead architectural decisions for data platforms, ensuring alignment with long-term scalability and reliability goals.
- Implement best practices in software engineering, including version control, CI/CD, automated testing, and security protocols.
- Promote data quality and system observability using modern tools such as Airflow, dbt, and Spark.
Requirements
- Minimum of 5 years of hands-on experience in data engineering roles.
- Strong background in data warehouse and data lake architectures.
- Proficiency in Python and SQL, with experience building automated, production-grade data pipelines.
- Familiarity with cloud platforms, particularly AWS or GCP.
- Experience with data processing frameworks such as Spark, Athena, or Pandas.
- Working knowledge of data orchestration tools, preferably Airflow.
- Understanding of relational database design and experience with platforms like Snowflake or Redshift.
Preferred Qualifications
- Production experience handling very large datasets.
- Hands-on work with AWS big data services like EMR, Glue, and EC2.
- Experience with Infrastructure as Code tools such as Terraform or CloudFormation.
- Familiarity with BI and analytics platforms like Tableau, Looker, or Power BI.
- Track record of upholding high engineering standards and driving technical innovation.
- Interest in emerging technologies including Apache Iceberg, Dagster, DBT, 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.
Benefits
- Annual salary reviews based on performance and business outcomes.
- 99% discount on personal shipments via Packlink.pro.
- Up to 500 PLN per year in matched donations to NGOs of your choice.
- One paid volunteer day per year.
- Referral bonuses ranging from 4,000 to 20,000 PLN based on role complexity.
- Free psychological support through an Employee Assistance Program.
- Flexible work hours and hybrid work model with company-provided equipment for remote work.
- Up to 7,000 PLN per year for training, certifications, and conference attendance.
- Free access to online learning platforms like LinkedIn Learning.
- Up to 30 days of vacation annually, with additional days earned over time.
- Weekly language classes in English, Spanish, and German.
- Free private medical and life insurance.
- Co-financing for sports, gym memberships, and recreational activities.
- Modern offices in Zielona Góra and Wrocław with complimentary snacks and beverages.
