Job Description
Job DescriptionStrong SQL Developer with an understanding of Data Build Tool (DBT)
Responsibilities:
Data Transformation and Modeling:
- Design and implement data transformations and models using data to create structured, cleaned, and aggregated datasets.
- Develop and maintain data models that accurately represent business logic and data requirements.
SQL Expertise:
- Write and optimize SQL queries within dbt to extract, manipulate, and join data from various sources (e.g., databases, APIs, flat files).
- Ensure SQL code follows best practices for readability, performance, and maintainability.
Version Control:
- Use version control systems (e.g., Git) to manage dbt codebase, enabling collaborative development and tracking changes over time.
- Collaborate with data engineers and analysts to coordinate code changes.
Testing and Documentation:
- Implement unit tests within dbt to verify the accuracy and reliability of data transformations.
- Document dbt models, data lineage, and transformations to facilitate understanding and collaboration.
Automation:
- Schedule and automate dbt runs to keep data models up-to-date and synchronized with source systems.
- Implement data orchestration and scheduling as needed.
Data Quality Assurance:
- Develop and enforce data quality checks and validations within dbt to identify and rectify data issues.
- Monitor data quality and integrity, responding to anomalies or discrepancies.
Performance Optimization:
- Optimize dbt models and queries for performance, identifying and addressing bottlenecks.
- Analyze and fine-tune data processing pipelines to meet performance requirements.
Collaboration:
- Collaborate closely with data engineers, data analysts, and business stakeholders to understand data requirements and deliver data solutions.
- Participate in cross-functional teams and contribute to data-related projects.
Security and Compliance:
- Ensure data security and compliance with relevant data protection regulations (e.g., GDPR, HIPAA) through appropriate data handling practices.
Knowledge Sharing:
- Share knowledge of dbt best practices and data modeling techniques with team members.
- Provide training and support to data analysts and other users of dbt.
Qualifications:
- Bachelor's or master's degree in computer science, data science, or a related field.
- Strong proficiency in SQL and experience working with relational databases.
- 3+ years of experience using dbt for data transformation and modeling in a data warehouse environment (e.g., Snowflake, BigQuery, Redshift).
- 7+ years of experience building business rules using a business rules engine similar to dbt
- Familiarity with version control systems (e.g., Git) and code collaboration workflows.
- Excellent data analysis and problem-solving skills.
- Strong attention to detail and a commitment to data quality.
- Understanding of data warehousing concepts and best practices.
- Knowledge of data governance and data security principles.
- Effective communication and collaboration skills to work with diverse teams.
- Experience with other data tools and languages (e.g., Python, R, Looker) is a plus.