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