Join our Data Engineering Team at Kraken! We’re seeking a skilled Data Engineer to join our Data Platform team and help us architect the future of Kraken’s data ecosystem. As a Data Engineer at Kraken, you’ll be responsible for building and maintaining high-performance data pipelines, ensuring the reliability and scalability of our data infrastructure, and enabling teams across the company to access clean, consistent, and timely data. You’ll work with modern technologies and large-scale datasets, playing a key role in making data accessible for analytics, machine learning, and product innovation. Responsibilities include building scalable and reliable data pipelines that collect, transform, load and curate data from internal systems; augmenting the data platform with data pipelines from external systems; ensuring high data quality for pipelines and making them auditable; driving data systems to be as near real-time as possible; supporting design and deployment of distributed data store that will be central source of truth across the organization; building data connections to company's internal IT systems; developing, customizing, and configuring self-service tools that help our data consumers to extract and analyze data from our massive internal data store; evaluating new technologies and building prototypes for continuous improvements in data engineering.
Data Engineer - Data Platform at Kraken
Remote - United States, Brazil, Chile, Mexico
Salary
USD 110,000 - 176,000/year
Requirements
Experience
- 5+ years of relevant experience
Skills
- Data engineering
- Data lake
- Data warehousing
- Python
- Scala
- Airflow
- SQL
- Spark/PySpark
- Apache Spark
- Kafka
- Apache Flink
- Software design principles
- Business requirements gathering
Responsibilities
- Build scalable and reliable data pipelines that collect, transform, load and curate data from internal systems
- Augment data platform with data pipelines from external systems.
- Ensure high data quality for pipelines you build and make them auditable.
- Drive data systems to be as near real-time as possible.
- Support design and deployment of distributed data store that will be central source of truth across the organization.
- Build data connections to company's internal IT systems.
- Develop, customize, configure self service tools that help our data consumers to extract and analyze data from our massive internal data store.
- Evaluate new technologies and build prototypes for continuous improvements in data engineering.
Technologies
PrestoAthenaGluePythonScalaAirflowSparkPySparkApache SparkKafkaApache Flink
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