Data Engineer

WEFORGE CONSULTING SERVICES INC.,
Woodbridge Township, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 139K

Job location

Woodbridge Township, United States of America

Tech stack

Airflow
Amazon Web Services (AWS)
Azure
Cloud Computing
Information Engineering
ETL
Data Warehousing
Python
Operational Databases
Power BI
Software Tools
Standard Sql
SQL Databases
Tableau
Unstructured Data
Google Cloud Platform
Azure
Snowflake
Spark
Database Performance
GIT
Data Lake
PySpark
Kubernetes
Kafka
Data Pipelines
Docker
Databricks

Job description

We are looking for a Data Engineer with 3+ years of experience in building and maintaining scalable data pipelines. The ideal candidate will have expertise in Python, SQL, cloud platforms, and modern data engineering tools to support enterprise analytics and business intelligence initiatives., * Develop and maintain ETL/ELT pipelines.

  • Design and optimize data models.
  • Build scalable data processing workflows.
  • Ensure data quality, integrity, and availability.
  • Work with structured and unstructured datasets.
  • Optimize database performance.
  • Collaborate with data analysts, software engineers, and business stakeholders.
  • Monitor and troubleshoot production data pipelines.
  • Document technical solutions and best practices., * Azure Data Factory
  • Databricks
  • Snowflake
  • Delta Lake
  • Apache Airflow
  • Kafka
  • Docker
  • Kubernetes
  • Power BI or Tableau

Skills

  • Data Engineering
  • Python
  • SQL
  • PySpark
  • Apache Spark
  • ETL
  • Azure Data Factory
  • Databricks
  • Snowflake
  • Delta Lake
  • Airflow
  • Kafka
  • AWS
  • Azure
  • Docker
  • Kubernetes
  • Git

Pay: $115,564.41 - $139,174.34 per year

Requirements

  • 3+ years of Data Engineering experience.
  • Strong SQL and Python skills.
  • Experience with Spark or PySpark.
  • Experience with Azure, AWS, or Google Cloud.
  • Experience building ETL/ELT pipelines.
  • Knowledge of relational and data warehouse concepts.
  • Experience with Git.
  • Strong problem-solving and communication skills.

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