A growing technology company is seeking a Senior Data Engineer to work in a hybrid setting. The ideal candidate will have over 5 years of experience in data engineering and proficiency in SQL, Python, and ETL frameworks. Responsibilities include designing data pipelines, conducting ad hoc analyses, and ensuring data quality. The role offers a chance to innovate within a small team and demands excellent communication skills to convey complex insights to stakeholders. Enthusiasm for blockchain technologies is a plus.
Qualifications
5+ years of experience in data engineering, software engineering, or machine learning.
Strong understanding of modern data warehousing and ETL frameworks.
Ability to analyze large datasets using SQL and validate data.
Responsibilities
Design and maintain data pipelines for the Stellar network.
Conduct data analysis to provide insights.
Improve observability and quality of data marts.
Skills
Data engineering
SQL
Python
Communication
ETL frameworks
Tools
Apache Airflow
GCP data stack
Databricks
Job description
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.