Sr. Data Engineer

Company provides cutting-edge trade surveillance technology that protects investors, enhances transparency, and ensures regulatory compliance across traditional financial assets and crypto markets.

Salary: 80 - N/A per hour
Location: USA, Los Angeles
Employment option: Remote
Job type: Full time

Job Summary:
Company provides cutting-edge trade surveillance technology that protects investors, enhances transparency, and ensures regulatory compliance across traditional financial assets and crypto markets.

Skills

Must Have

Hard skills:

• beginner in: Testing, Machine Learning, Azure, BI, Agile
• competent in: Snowflake
• proficient in: Service Level Agreement SLA, ClickHouse, Data Engineering, BigQuery, Prometheus, SQL, JAVA, Redis, Data Pipelines, Kafka, Apache, Grafana
• expert in: ETL, Databases

Soft skills:

• competent in: Communication Skills

Nice-to-have

Hard skills:

• beginner in: Data Warehousing, Information Security
• competent in: Big Data, Spark, AWS, Pipeline
• proficient in: Monitoring, Python

Job Description

Additional Requirements

We’re looking for a strong Senior Software Engineer with Data Engineering experience. Someone who is proficient in building robust, scalable, maintainable and thoroughly monitored data pipelines on cloud environments.

As a young and ambitious company in an extremely dynamic space, we pride ourselves on being independent, accountable, and organized, have a self-starter attitude, and be willing to get their hands dirty with day-to-day work that might be out of their official scope, while keeping an eye on their goals and the big picture.

Responsibilities

1. Design and develop the data's team micro services - Java services running on K8S.
2. Tackle data duplication, velocity, schema adherence (and schema versioning), high availability, data governance, and more.
3. Develop, design, and maintain end-to-end ETL workflows, including data ingestion and transformation logic, involving different data sources.
4. Enrich financial data through third-party data integrations.
5. Develop and maintain our data pipeline written mostly in Java and running on K8S in a micro-service architecture.
6. Plan and communicate integrations with other teams that consume the data and use it for insights creation.
7. Ongoing improvement of the way data is stored and served. Improve queries and data formats to make sure the data is optimized for consumption by a variety of clients.