What is this role?
As a Senior Data Engineer at Cirkul, you will play a critical role in designing, building, and maintaining our data infrastructure. You will work closely with data scientists, analysts, and software engineers to develop data pipelines, optimize performance, and ensure data integrity across our platforms. This is an exciting opportunity for a seasoned professional to contribute to impactful data projects and drive data strategy for a rapidly growing company.
The Senior Data Engineer will ensure an optimal delivery of initiatives across Data Pipeline Design and Development, Data Warehousing and Modeling, and Performance Optimization. They will also mentor data engineers on the team and collaborate cross functionally to set the strategic roadmap and execute.
What does an average day look like?
Driving Results:
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python and/or Node.js, SQL (using dbt for transformation), commercial SaaS and OSS offerings, and AWS big data technologies
Taking Ownership:
- Integrate DevOps/SRE practices on the data team by solving for performance, monitoring, and alerting
Making Decisions:
- Create and maintain optimal data pipeline architecture
Cultivating Relationships:
- Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs
Instilling Trust:
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Customer Focus:
- Manage infrastructure and configuration of data platform in the Cloud, ensuring health, reliability and uptime
What background should you have?
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree strongly preferred.
- 5+ years of experience in a Data Engineer role at a fast-paced organization with a proven track record of designing and implementing data pipelines, data warehouses, and data models
- Strong experience with SQL and NoSQL databases, including expertise in performance tuning and optimization.
- Hands-on experience with cloud data platforms (e.g., AWS Redshift, Google BigQuery, Azure Synapse) and data processing frameworks (e.g., Apache Spark, Kafka).
- Experience with programming languages such as Python, Java, or Scala.
- Proficiency in ETL tools and frameworks, such as Apache Airflow, Luigi, or similar.
- Experience with data integration tools and techniques, including RESTful APIs and data ingestion methods.
- Knowledge of data visualization tools and reporting platforms (e.g., Tableau, Looker, Power BI) is a plus.
- Experience with modern columnar data warehouses such as Snowflake, Redshift, BigQuery
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- Strong project management and organizational skills
- Experience supporting and working with cross-functional teams in a dynamic environment