Data Engineer (DBT, Databricks & SQL Exp)

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

Agile Methodologies
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data Architecture
Information Engineering
Data Governance
Data Infrastructure
Data Integrity
ETL
Data Transformation
Data Systems
Database Queries
DevOps
Identity and Access Management
SQL Databases
Data Streaming
Strategies of Testing
Workflow Management Systems
Data Build Tool (dbt)
Spark
GIT
Data Lake
Amazon Web Services (AWS)
Software Version Control
Data Pipelines
Databricks

Job description

  • Design, build, and optimize robust and scalable data pipelines using Databricks and DBT on AWS.
  • Develop, deploy, and maintain ELT/ETL processes to transform raw data into actionable insights.
  • Collaborate with data analysts, data scientists, and business stakeholders to understand requirements and deliver data solutions.
  • Ensure data integrity, quality, and governance across all data flows.
  • Continuously monitor and improve performance, reliability, and cost-efficiency of data pipelines.
  • Write and maintain high-quality documentation.

Requirements

We are seeking a highly experienced Senior Data Engineer with 12+ years of hands-on experience in data engineering and data pipeline development. The ideal candidate will have strong expertise in Databricks, DBT, AWS, and Apache Spark, and a proven track record of working with modern data platforms in large-scale enterprise environments.

This role requires a professional who is adept at building scalable data pipelines, transforming data using DBT, working extensively with AWS cloud infrastructure, and developing in a Spark/Databricks environment. Strong SQL query writing skills are essential.

Mandatory Skills & Experience:

  • 12+ years of experience in data engineering or relevant fields.
  • Expert-level knowledge of Databricks - including notebooks, jobs, Delta Lake, and workspace management.
  • Strong hands-on experience with DBT (Data Build Tool) - including writing models, tests, and documentation.
  • Proficiency in AWS services - including S3, Glue, Redshift, Lambda, IAM, etc.
  • Strong experience with Apache Spark - both batch and streaming data processing.
  • Strong experience writing efficient SQL queries for data transformation and analysis.
  • Proven ability to work independently in a remote environment.
  • Solid understanding of data modeling, ETL/ELT processes, and modern data architecture.
  • Experience in version control (Git), CI/CD pipelines, and Agile methodologies., * AWS Certification (e.g., AWS Data Analytics, AWS Solutions Architect)
  • Experience with orchestration tools like Airflow or AWS Step Functions.
  • Familiarity with DevOps practices in a data environment.
  • Exposure to data quality frameworks and testing strategies.

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