Data Engineer with DBT

Trebecon LLC
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote

Tech stack

Amazon Web Services (AWS)
Azure
Batch Processing
Big Data
Continuous Integration
Information Engineering
ETL
Data Transformation
Data Warehousing
Distributed Computing Environment
Distributed Systems
Performance Tuning
Scrum
Query Optimization
SQL Stored Procedures
SQL Databases
Google Cloud Platform
Cloud Platform System
Data Build Tool (dbt)
Spark
GIT
Containerization
Data Lake
PySpark
Optimization Algorithms
Data Pipelines
Databricks

Requirements

SQL, DBT, Databricks, Apache Spark, AWS, * 10+ years of professional experience as a Data Engineer.

  • Strong hands-on experience with Apache Spark / PySpark for large-scale distributed data processing.
  • Strong experience with DBT (Data Build Tool) for data transformation and modeling.
  • Hands-on experience with Databricks for data engineering, Spark-based processing, and pipeline development.
  • Proficiency in SQL including query optimization, performance tuning, data modeling, and stored procedures.
  • Experience building scalable ETL/ELT pipelines using Spark and cloud-native technologies.
  • Experience with at least one cloud platform such as AWS, Azure, or Google Cloud Platform (AWS preferred).
  • Strong understanding of data warehouse, lakehouse, and data lake architectures.
  • Experience working with large datasets, batch processing, and real-time/streaming data pipelines.
  • Knowledge of Delta Lake, Spark optimization techniques, and distributed computing concepts is preferred.
  • Experience with Git, CI/CD pipelines, and Agile/Scrum methodologies.
  • Excellent problem-solving, analytical, and communication skills.

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