Senior Data Engineer (Hybrid)

Overview

About the job Senior Data Engineer (Hybrid). Note: This position does not offer any visa sponsorship.

Responsibilities Design, build, orchestrate, and maintain data pipelines to provide unique insights into the liquidity, adoption, and usage of the Stellar network. Conduct ad hoc data analysis to clean, transform, and distill key insights about the Stellar Network. Improve the observability and maintainability of our data marts, ensuring data usage, quality, and freshness. Translate business priorities and community requests into data products that support data-driven decision-making. Enhance data accessibility by promoting the self-service adoption of dashboards, KPIs, and SQL interfaces. Required Skills 5+ years of professional experience in data engineering, machine learning, or software engineering. Strong understanding of modern data warehousing concepts and hands-on experience with ETL frameworks such as dbt, Fivetran, Databricks, or Talend. Demonstrated ability to analyze large datasets using SQL to validate data and extract insights. Expertise with ETL schedulers like Apache Airflow, Dagster, AWS Glue, or similar frameworks. Proficient programming skills in languages such as Python or Golang. Excellent communication skills, capable of explaining complex data insights to non-technical stakeholders. Enthusiasm for working in a small, growing team with the freedom to innovate and set direction. Desirable Skills and Experience Cloud development experience, particularly with the GCP data stack. Proficiency with CI/CD pipelines. Experience in administering BI tools and building compelling visualizations. Understanding of data governance best practices including data cataloging, quality control, and usability. Strong interest in blockchain technologies and cryptocurrencies, with a basic understanding of these systems.

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