Data Platform Engineer (AWS)

• Industry: automotive • Rate: up to 170 pln/h net + VAT, B2B • Location: fully remote We are seeking an experienced Data Platform Engineer to design and implement a cloud-based data lakehouse platform ingesting engineering and security data, transforming it across medallion layers, and serving it to analytics dashboards and AI agents. Responsibilities: • Design and build cloud-based data lakehouse architectures. • Ingest and transform engineering and security data through multiple layers. • Deliver production-grade data platforms to support analytics and AI functionality. • Collaborate with data scientists and DevOps engineers to optimize data workflows. • Explain technical trade-offs to non-technical stakeholders. Required Experience • 5+ years in data engineering • 2+ years building lakehouse architectures (Bronze/Silver/Gold or equivalent) • Delivered production-grade data platforms • Experience with graph databases (Neo4j, Amazon Neptune, TigerGraph) • Hands-on with stream processing (Kafka, Flink, Spark Streaming, Kinesis) Core Technical Skills • Cloud: AWS (S3/Blob, RDS/SQL DB, Managed Kafka, Serverless compute) • SQL & Modeling: SQL, dimensional modeling, SCD2, normalization/denormalization • Transformations: dbt, Databricks SQL, Dataform, SQL/Python frameworks • Programming: Python, Scala • Orchestration: Airflow, Prefect, Dagster, Step Functions, Azure Data Factory • IaC: Terraform, CloudFormation, Pulumi, ARM Nice to have: • Search: OpenSearch, Elasticsearch, Solr • Graph: Cypher, SPARQL, Gremlin, graph ETL • Data Quality: Great Expectations, dbt tests, custom validators • Real-time: Flink, Spark Streaming, Lambda, Cloud Functions • Monitoring: Grafana, Datadog, CloudWatch