Key Responsibilities
- Design, build, and maintain scalable and efficient ETL/ELT pipelines using DBT and Databricks.
- Develop, optimize, and troubleshoot complex SQL queries for data transformations, validations, and reporting.
- Collaborate with data analysts, data scientists, and business stakeholders to understand data needs.
- Implement data quality and data governance best practices in pipelines.
- Work with structured and semi-structured data from multiple sources (e.g., APIs, flat files, cloud storage).
- Build and maintain data models (star/snowflake schemas) to support analytics and BI tools.
- Monitor pipeline performance and troubleshoot issues in production environments.
- Maintain version control, testing, and CI/CD for DBT projects using Git and DevOps pipelines.
Required Skills & Experience
- experience as a Data Engineer
- Strong experience with DBT (Cloud or Core) for transformation workflows.
- Proficiency in SQL — deep understanding of joins, window functions, CTEs, and performance tuning.
- Hands-on experience with Databricks (Spark, Delta Lake, Notebooks).
- Experience with at least one cloud data platform: AWS (Redshift), Azure (Synapse), or Google Cloud Platform (BigQuery).
- Familiarity with data lake and lakehouse architecture.
- Experience with Git and version control in data projects.
- Knowledge of orchestration tools like Airflow, Azure Data Factory, or dbt Cloud scheduler.
- Comfortable with Python or PySpark for data manipulation (bonus).
Rate:
Not specified
Location:
Remote
IR35 Status:
Outside
Remote Status:
Remote
Industry:
Data & Analytics
Seniority Level:
Not Specified