T

Senior Data Engineer - Cloud Data Platform

trebecon llc United State
Remote
This Job is No Longer Active This position is no longer accepting applications
AI Summary

Design and implement scalable data pipelines using DBT and Databricks. Develop and optimize complex SQL queries. Collaborate with stakeholders to understand data needs.

Key Highlights
Design and build scalable and efficient ETL/ELT pipelines using DBT and Databricks
Develop and optimize 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
Monitor pipeline performance and troubleshoot issues in production environments
Technical Skills Required
DBT Databricks SQL Python PySpark Git Delta Lake Spark AWS Azure GCP Airflow Azure Data Factory dbt Cloud scheduler

Job Description


Job Title: Data Engineer – DBT, Databricks & SQL Expert

Location: Remote


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 GCP (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).




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