Terraform (nice to have)
CodeFresh (nice to have)
Docker (nice to have)
GitHub (nice to have)
AWS services (advanced)
Dear Data Engineer,
Help people save in the healthcare aspect. Work to improve a platform that tracks prescription drug prices.
The platform is available in the U.S. market, has many users, and processes millions of data, checking over 75,000 pharmacies in the United States.
Collaborate with product managers, data scientists, data analysts, and engineers to define requirements and data specifications.
Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, EMR.
Develop, deploy, and maintain serverless data pipelines using Event Bridge, Kinesis, AWS Lambda, S3, and Glue.
Define and manage the overall schedule and availability for a variety of data sets.
Work closely with other engineers to enhance infrastructure, improve reliability and efficiency.
Make smart engineering and product decisions based on data analysis and collaboration.
Act as in-house data expert and make recommendations regarding standards for code quality and timeliness.
Architect cloud-based data infrastructure solutions to meet stakeholder needs.
Skills & Qualifications :
Bachelor’s degree in analytics, statistics, engineering, math, economics, computer science, information technology, or related discipline.
5+ years of professional experience in the big data space.
5+ years experience in engineering data pipelines using big data technologies (Spark, Flink, etc.) on large-scale data sets.
Expert knowledge in writing complex SQL and ETL development with experience processing extremely large datasets.
Expert in applying SCD types on S3 data lake using Delta Lake / Hudi.
Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions.
Deep familiarity with AWS Services (S3, Event Bridge, Glue, EMR, Redshift, Lambda).
Ability to quickly learn complex domains and new technologies.
Good To Have :
Experience with customer data platform tools such as Segment.
Experience using Jira, GitHub, Docker, CodeFresh, Terraform.
Experience contributing to full lifecycle deployments with a focus on testing and quality.
Experience with data quality processes, data quality checks, validations, data quality metrics definition, and measurement.
Salary 25000 PLN / B2B / 5500 EUR / B2B
Work 100 % remotely,
Flexible working hours,
20 days off with full pay.
Don't wait - apply - you have nothing to lose, you can only gain!