Senior Software Engineer (Reporting and Analytics Developer)

We are seeking a Data Engineer. You will design, build and optimize data pipelines, models and reporting solutions that power enterprise analytics. You’ll work with SQL, Python, Spark and ETL tools, improve data collection and consumption, support deployments and production issues and use AI-assisted development and automation to boost delivery efficiency and maintain reliable operations.

Responsibilities

• Analyze data needs, document requirements and translate them into technical solutions
• Design, build and optimize data pipelines and data models for analytics and reporting
• Migrate and streamline data collection and consumption through more efficient channels
• Develop dashboards and reports aligned to user needs and governance standards
• Create test plans and scripts, support system testing and user acceptance testing
• Partner with technical teams to deploy solutions, support adoption and ensure stable operations
• Troubleshoot production issues across data pipelines, platform resources and application logs
• Use AI coding tools and automation to improve build, test, deployment and code quality

Requirements

• Relevant senior-level experience, ideally 9 years or more delivering data engineering solutions in enterprise environments
• Strong SQL with proven ability in data modeling and data analysis
• Hands-on experience with Python including scripting for data workflows
• Experience building big data pipelines using PySpark, Linux and enterprise ETL tools (e.g., Informatica)
• Experience with Cloudera Data Platform including Hive and Impala in production environments
• Experience delivering reports and dashboards using tools such as Tableau or SAP BusinessObjects
• Understanding of analytics and data warehouse implementations including operational support needs
• Ability to troubleshoot complex issues from system resources to application stack traces
• Working knowledge of Agile or Waterfall delivery with clear documentation practices

Nice to have

• Experience with data virtualization tools such as Denodo
• Experience with DevOps practices for deployment automation and release management
• Hands-on experience using AI engineering tools (e.g., GitHub Copilot) for reviews, refactoring and documentation