Senior Data Platform Engineer, Data Cloud

This is a fully remote position, open to applicants in New Hampshire, +5 more states.

📋 Description

• Contribute to defining the technical vision for the team/organization and articulate the potential evolution of our data platform and architecture.

• Design, implement, and refine our high-performance, scalable data serving platform that facilitates data querying and consumption throughout the organization as well as for external data products.

• Create, implement, and enhance our high-performance, scalable data storage and transformation platform that supports both batch and stream processing, managing over 100 million updates daily on datasets exceeding 100 billion rows.

• Develop seamless integrations between Data Cloud and an array of relational and noSQL OLTP databases.

• Construct batch and streaming data pipelines for essential blockchain datasets extensively utilized across the company.

• Deploy scalable cloud infrastructure with enterprise-grade reliability, implement and uphold infrastructure automation and self-service capabilities, and develop robust CI/CD pipelines.

• Establish and uphold observability, security, and data governance solutions to guarantee the high quality, efficiency, and reliability of data pipelines.

⛳️ Requirements

• Over 6 years of experience as a Data Platform Engineer, Data Engineer, or Data Infrastructure Engineer, with practical expertise in building and maintaining large-scale cloud-based data platforms.

• A passion for leading or contributing to the technical vision of the team/organization, a strong sense of ownership over mission-critical systems, and a commitment to enhancing their skills while mentoring others.

• Experience in constructing and managing both batch and streaming data pipelines with tools such as DBT, Databricks, Apache Spark, and Apache Flink, alongside a solid understanding of data architecture and best practices in data modeling.

• Proficient in AWS services, cloud architecture, and fault-tolerant distributed data systems, with expertise in using Terraform for provisioning and managing cloud infrastructure.

• A comprehensive understanding of modern data lakehouse architectures and ecosystems like Kafka, Flink, Spark, Databricks, Snowflake, DBT, Airflow, Debezium, Delta/Iceberg, StarRocks, Clickhouse, along with proficiency in Python/Java and SQL.

• Experience in creating tools and frameworks to enhance the development of data pipelines, along with familiarity with best practices in data governance, data quality, and observability.

🏝️ Benefits

• Offers Equity

• Offers Bonus