Responsible for maintaining and enhancing data warehouses and pipelines, developing scalable ETL processes, data analysis, and reporting through visualization tools like PowerBI.
Job Overview
We are seeking a skilled Data Engineer to join our team and drive our data infrastructure forward. In this role, you will primarily focus on maintaining and enhancing our data warehouse and pipelines (80%) while also contributing to data analysis and reporting initiatives (20%). You'll work closely with cross-functional stakeholders to build robust data solutions and create actionable insights through compelling visualizations.
Key Responsibilities
Data Engineering
- Infrastructure Management: Maintain, enhance, and optimize existing data warehouse architecture and ETL pipelines.
- Pipeline Development: Design and implement scalable ETL/ELT processes ensuring data quality, integrity, and timeliness.
- Performance Optimization: Monitor and improve pipeline performance, troubleshoot issues, and implement best practices.
- Documentation: Create and maintain comprehensive documentation for data engineering processes, architecture, and configurations.
Data Analysis & Reporting
- Stakeholder Collaboration: Partner with business teams to gather requirements and translate them into technical solutions.
- Report Development: Build and maintain PowerBI dashboards and reports that drive business decisions.
- Data Modeling: Develop new data models and enhance existing ones to support advanced analytics.
- Insight Communication: Transform complex data findings into clear, actionable insights for various departments.
Required Qualifications
Technical Skills
- Programming & Query Languages: Strong proficiency in Python, SQL, and PySpark.
- Big Data Platforms: Experience with cloud data platforms including Snowflake, BigQuery, and Databricks. Databricks experience highly preferred.
- Orchestration Tools: Proven experience with workflow orchestration tools (Airflow preferred).
- Cloud Platforms: Experience with AWS (preferred), Azure, or Google Cloud Platform.
- Data Visualization: Proficiency in PowerBI (preferred) or Tableau.
- Database Systems: Familiarity with relational database management systems (RDBMS).
Development Practices
- Version Control: Proficient with Git for code management and collaboration.
- CI/CD: Hands-on experience implementing and maintaining continuous integration/deployment pipelines.
- Documentation: Strong ability to create clear technical documentation.
Experience & Communication
- Professional Experience: 3+ years in data engineering or closely related roles.
- Language Requirements: Fluent English communication skills for effective collaboration with U.S. based team members.
- Pipeline Expertise: Demonstrated experience building and maintaining production data pipelinesk
Top Skills
AWS
Azure
BigQuery
Databricks
Git
Google Cloud Platform
Power BI
Pyspark
Python
Snowflake
SQL
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