Engineering Manager, Data Platform

This is a fully remote position, open to applicants in California.

📋 Description

• Lead and develop a team of impactful engineers, providing guidance in both technical and cultural dimensions.

• Offer consistent coaching and technical mentorship to your immediate team, while also contributing to the growth of the wider engineering department.

• Take direct responsibility for ensuring the quality and timely delivery of the team's outputs, while managing the availability and performance of essential services.

• Drive projects that are aligned with clearly defined objectives and measurable results, being accountable for key performance indicators (KPIs).

• Promote best practices in design and usability, developing scalable solutions while prioritizing documentation and knowledge sharing.

• Address operational escalations and collaborate with various teams to resolve production incidents until they are fully addressed.

• Contribute to the development of highly reliable data services that integrate seamlessly with multiple blockchains.

• Engineer and optimize ETL pipelines for real-time transformation and processing of petabytes of both structured and unstructured data.

• Design data models to ensure efficient storage and retrieval, maintaining sub-second latency for querying blockchain data.

• Oversee the deployment and active monitoring of large-scale database clusters, with a focus on performance and high availability.

• Work cross-functionally with data scientists, backend engineers, and product managers to design, implement, and enhance new data models in support of TRM’s products.

⛳️ Requirements

• A Bachelor's degree (or equivalent) in Computer Science or a related discipline.

• A proven history of over 5 years in designing and implementing distributed system architecture, from conception through to production.

• Proficiency in Python programming along with strong skills in SQL or SparkSQL.

• Versatility across the complete range of data engineering, including:

• - Expertise in data stores such as ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j.

• - Experience with data pipeline and workflow orchestration tools like Airflow, DBT, Luigi, Azkaban, and Storm.

• - Advanced skills in data processing technologies and streaming workflows, such as Spark, Kafka, and Flink.

• - Competence in deploying and meticulously monitoring infrastructure within public cloud platforms, utilizing tools like Docker, Terraform, Kubernetes, and Datadog.

• A demonstrated ability to navigate the complexities of loading, querying, and transforming large and intricate datasets.

🏝️ Benefits

• Competitive salary

• Remote work options