SS&C is seeking a skilled Data Engineer to join their team, focusing on designing, building, and maintaining data infrastructure to support business decision-making. This role emphasizes data engineering expertise while incorporating elements of data analysis, leveraging tools like GitHub, Kubernetes, and Grafana to ensure high-quality, accessible data for stakeholders.
Requirements
- Strong proficiency in SQL and Python for data processing and transformation.
- Experience with data engineering tools such as Airflow or similar.
- Proficiency in using GitHub for version control, code collaboration, and managing data repositories.
- Hands-on experience with Kubernetes for deploying and managing containerized data applications.
- Proficiency in Grafana for creating and managing dashboards to monitor data systems.
- Knowledge of data architecture principles, including data modeling and ETL processes.
- Experience with visualization tools like Grafana to assist in data delivery.
Responsibilities
- Design, develop, and maintain data infrastructure to collect, store, and process data from various sources.
- Transform raw data into reliable, high-quality, and accessible formats for use by business stakeholders.
- Use GitHub for version control, collaboration, and documentation of data scripts and infrastructure code.
- Perform data extraction and transformation using tools like SQL or Python to support analytical needs.
- Develop and maintain documentation for data processes in GitHub repositories to ensure reproducibility.
- Support the creation of reports and dashboards by ensuring data is structured and accessible for visualization tools like Tableau, Power BI, or Grafana.
- Deploy and manage data workflows in Kubernetes clusters to ensure reliability and fault tolerance.
Other
- Collaborate with cross-functional teams, including business stakeholders, to understand data requirements and deliver tailored solutions.
- Strong problem-solving skills to optimize data processes.
- Effective communication skills to collaborate with technical and non-technical stakeholders.
- Understanding of data analysis techniques to support business reporting.
- Familiarity with data querying to support analytical workflows.
