AWS Data Engineer

In Cyclad we work with top international IT companies in order to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We’re looking for an experienced AWS Data Engineer to join our growing data team and help shape our data platform's future. Our platform leverages AWS Step Functions, EMR (PySpark), Glue, Lambda, S3, Redshift, dbt, Airflow, and Looker to deliver trusted, scalable data solutions. As part of the data team, you will play a key role in supporting the day-to-day operation of the platform while driving strategic improvements in reliability, scalability, cost optimization, and machine learning capabilities.

Project information:

• Industry: IT Services

• Office location: Poland

• Remote work: 100% remote from Poland

• Budget: b2b 140 – 170 PLN/h net

• Seniority: Mid and Senior

• Project length: till 06.2027, with the possibility to extend it

• Only candidates with citizenship in the European Union and residence in Poland

• Start date: ASAP

Project scope:

• Support daily platform operations, including pipeline failures, data fixes, and new data requests

• Build, maintain, and optimize data pipelines using AWS, PySpark, SQL, and dbt.

• Develop and maintain ingestion processes (including new sources from the Rails service databases on Aurora Postgres and SQS)

• Own and evolve Segment tracking, event schemas, and downstream data integrations

• Ensure consistency between Redshift and platforms such as Braze, Amplitude, AppsFlyer, and Looker

• Optimize Redshift performance and cost

• Maintain our existing ML models, build feature pipelines and training datasets for new ones, and put them into production on SageMaker

• Support AI projects, including LLM-based tools (data access, evaluation datasets, cost control) and the Claude Code skills the analysts use for SQL and tracking specs

• Manage the platform as code (AWS SAM and CloudFormation) and contribute to CI/CD automation

• Agree metric definitions with analytics, finance, and product, and keep them consistent in the warehouse and Looker

• Improve dbt project with the analytics team: incremental models, source freshness checks, and broader tests

• Review code and mentor a junior engineer

Competence demands:

• 4+ years in data engineering, with ownership of a production warehouse

• Strong SQL and Python skills, including PySpark

• Hands-on experience with Redshift (performance tuning, dimensional modeling, SCDs)

• Strong knowledge of dbt (models, tests, sources, incremental processing)

• Experience with Segment or a similar customer data platform

• Solid AWS experience, including S3, IAM, Glue, Lambda, Step Functions, EMR, and Aurora/RDS

• Experience with Infrastructure as Code (CloudFormation, SAM, or Terraform) and CI/CD

• Proven track record building reliable, scalable data pipelines

• Hands-on experience getting data ready for ML or AI use (feature engineering, training data, or model serving), even if you haven’t owned a full ML system

• English: min. B2

Nice to have:

• Experience with Braze, Amplitude, AppsFlyer, or similar tools

• Knowledge of marketing attribution and lifecycle data

• SageMaker or MLOps platforms

• Exposure to LLM applications (Bedrock, OpenAI, Anthropic APIs) or AI-assisted development tools

• Looker/ LookML

• Airflow, including migrating or retiring legacy pipelines

• Redshift Spectrum, data sharing, and warehouse cost optimization

• Experience working with subscription, payments, revenue, and churn data.

• Integrating third-party APIs and vendor data exports (rate limits, schema changes, retries)

We offer:

• Remote working model

• Dynamic and innovation-driven engineering environment

• Full-time job agreement based on b2b

• Private medical care with dental care (covering 70% of costs)

• Multisport card (also for an accompanying person)

• Life insurance