Overview

Join our innovative team as a Data Engineer and become a vital driver of our data-driven decision-making process! In this role, you will design, develop, and maintain scalable data pipelines and architectures that empower business insights and strategic initiatives. Your expertise will enable seamless data integration across diverse platforms, ensuring high-quality, accessible data for analytics, reporting, and machine learning applications. If you thrive in a fast-paced environment where your technical skills make a real impact, this opportunity is perfect for you!

Responsibilities

Develop, implement, and optimize ETL (Extract, Transform, Load) pipelines to facilitate efficient data flow from various sources into centralized data warehouses or lakes.
Design and maintain robust data models and schemas using dimensional modeling techniques to support business intelligence tools and analytics.
Manage large-scale big data systems utilizing Hadoop, Spark, Hive, and other distributed processing frameworks to handle complex datasets.
Collaborate with cross-functional teams to understand data requirements and translate them into scalable solutions using cloud platforms such as AWS, Azure Data Lake, or other public cloud services.
Integrate data from diverse sources including SQL databases (Microsoft SQL Server, Oracle), cloud databases, and linked data environments to create unified datasets.
Write efficient SQL queries and scripts in Python or Bash for automation, analysis, and troubleshooting of data workflows.
Support the development of RESTful APIs for seamless data access and integration with external applications or services.
Ensure compliance with best practices in data management, security standards, and governance policies while maintaining high performance of data systems.

Experience

Proven experience designing and implementing data warehousing solutions using tools like Informatica, Talend, or similar ETL platforms.
Strong proficiency in SQL programming across various databases such as Microsoft SQL Server, Oracle, and cloud-based systems like Azure Data Lake or similar.
Hands-on experience working with big data technologies including Hadoop ecosystem components (Hadoop Distributed File System - HDFS), Spark, Hive, and related frameworks.
Demonstrated ability to develop scalable ETL pipelines using Python, Shell scripting (Bash), or other scripting languages within an Agile environment.
Familiarity with cloud computing platforms such as AWS or Azure Public Cloud for deploying and managing big data systems.
Knowledge of data modeling principles including dimensional modeling for designing efficient data warehouses supporting analytics needs.
Experience working with business intelligence tools like Looker or similar visualization platforms to translate complex datasets into actionable insights.
Strong analytical skills with the ability to troubleshoot issues quickly while maintaining high-quality standards in data management processes.

Embark on a journey where your technical expertise fuels innovation! We are committed to fostering an inclusive environment that supports your growth as a Data Engineer dedicated to transforming raw data into strategic assets that propel our organization forward.

Pay: $45.00 - $55.00 per hour

Work Location: In person

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