Principal BI Engineer - Data Modeling & Analytics Infrastructure
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes to ensure efficient data flow across systems.
- Architect and implement robust data warehouse solutions that support business intelligence and analytics initiatives.
- Create and optimize complex SQL queries to extract, transform, and analyze large datasets with high performance.
- Collaborate with cross-functional teams to understand data requirements and deliver appropriate technical solutions.
- Develop and maintain data models that accurately represent business processes and enable effective analytics.
- Implement data quality measures and monitoring systems to ensure data accuracy and reliability.
- Create compelling data visualizations and dashboards that effectively communicate insights to stakeholders.
- Apply statistical methodologies to identify trends, patterns, and anomalies in business data.
- Document data architecture, pipelines, and processes for knowledge sharing and continuity.
- Stay current with emerging technologies and best practices in data engineering and business intelligence.
Required Skills & Experience
- Proven experience (3+ years) as a Data Engineer, BI Developer, or similar role with demonstrated project success.
- Advanced SQL skills across various database systems, particularly MySQL and SQL Server.
- Strong understanding of data warehouse design concepts, including dimensional modeling and star schemas.
- Proficiency in designing and implementing ETL/ELT workflows for large-scale data processing.
- Experience with Python (preferred) or equivalent programming skills in Java or C# for data manipulation and analysis.
- Hands-on experience with data visualization tools and techniques to effectively present complex information.
- Solid foundation in statistics with the ability to apply statistical methods for data analysis.
- Knowledge of data quality management and governance principles.
- Experience working with cloud-based data platforms (AWS, Azure, or GCP).
- Excellent problem-solving abilities and attention to detail.
Nice to Have
- Experience with modern data stack technologies like Snowflake, BigQuery, or Redshift.
- Knowledge of streaming data processing using Kafka, Spark Streaming, or similar technologies.
- Familiarity with data orchestration tools such as Apache Airflow or Luigi.
- Experience with NoSQL databases like MongoDB, Cassandra, or DynamoDB.
- Understanding of data science workflows and machine learning pipelines.
- Experience with version control systems (Git) and CI/CD pipelines for data projects.
- Certifications related to data engineering, cloud platforms, or database management.
- Background in implementing data governance frameworks and data quality monitoring.
- Experience working in agile development environments.