Requirements

Expected technologies

SQL

GitHub

Jenkins

Jira

SonarQube

Snowflake Data Cloud

Optional technologies

Python

C#

Microsoft Azure

AWS

Operating system

Windows

Our requirements

• Snowflake expertise for data warehousing, query optimization, and analytics.
• Hands-on experience with Azure Data Factory for ETL and orchestration.
• Strong proficiency in SQL for data manipulation and analysis.
• Familiarity with software engineering lifecycle tools (GitHub, Jenkins, Jira, SonarQube).
• Understanding of CI/CD processes and modern DevOps practices.
• Solid understanding of the software development lifecycle (SDLC).
• Excellent communication and collaboration skills.

Optional

• Proficiency in Python or C# for automation and data workflows.
• Experience with anomaly detection techniques and statistical analysis.
• Knowledge of cloud platforms (Azure, AWS) and infrastructure monitoring.
• Understanding of the business of engineering.
• Ability to work independently and manage multiple priorities.

Your responsibilities

• Aggregate data from diverse engineering tools (CI/CD pipelines, code repositories, issue trackers, observability platforms).
• Integrate and manage data within Snowflake for scalable analytics and reporting.
• Design and maintain Azure Data Factory pipelines for data ingestion and transformation.
• Ensure data accuracy and consistency across all sources.
• Build dashboards and reports in Power BI or Tableau to monitor engineering health metrics (velocity, quality, reliability).
• Generate periodic and ad-hoc reports for leadership review.
• Anomaly Detection & Analysis
• Identify trends, anomalies, and outliers in engineering performance data.
• Conduct root cause analyses and collaborate with engineering teams to resolve issues.
• Partner with software engineering leaders to interpret insights and recommend actions.
• Communicate findings clearly to both technical and non-technical audiences.