Key skills
AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudETLGoogle Cloud PlatformJavaKafkaPythonSparkSQLTerraformTypeScriptAIELTAnalyticsSnowflakeRedshiftGCPGoogle CloudOpenTelemetry
About this role
Role Overview
- Help design, build, and maintain systems for commerce analytics platform
- Contribute to reliable data flows and scalable infrastructure
- Explore AI-assisted development workflows to improve speed and quality
- Design and evolve the data model across layers
- Manage streaming pipelines on Apache Flink and Kafka
- Oversee Iceberg lake and ClickHouse warehouse
- Handle batch processing with Prefect
- Ensure observability with OpenTelemetry traces and custom metrics
Requirements
- Proven, hands-on experience in the following areas:
- Big data fundamentals — partitioning, shuffles, skew, late-arriving data, exactly-once semantics, idempotency
- Stream processing — Apache Flink, Spark Structured Streaming, Kafka Streams, Beam
- Batch processing and orchestration — Prefect, Dagster, Airflow; ETL/ELT pipeline design
- Lakehouse formats — Iceberg, Paimon, Delta, Hudi; metadata management
- Analytical warehouses — ClickHouse, BigQuery, Snowflake, Redshift, DuckDB
- Data modeling concepts — medallion and mart architectures, dimensional modeling
- Cloud infrastructure — AWS, GCP, or Azure; infrastructure-as-code tools such as Terraform
- Engineering habits — instrumentation, testing data pipelines, schema governance
- Language-agnostic; experience with Python, Java, SQL, TypeScript is a plus.
Tech Stack
- Airflow
- Amazon Redshift
- Apache
- AWS
- Azure
- BigQuery
- Cloud
- ETL
- Google Cloud Platform
- Java
- Kafka
- Python
- Spark
- SQL
- Terraform
- TypeScript
Benefits
- Flexible work arrangements
- Professional development