Senior Azure Data Engineer

April 3

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Zealogics Inc

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Zealogics Inc. is a global technology company headquartered in New Jersey, specializing in IT consulting, engineering, and systems implementation. Founded in 2012, Zealogics provides a wide array of services, including software and hardware engineering, digital transformation, cloud solutions, artificial intelligence, and low-code development. The company aims to empower businesses across various industries such as semiconductor, automotive, finance, healthcare, telecom, and retail, with innovative and scalable solutions that enhance efficiency, agility, and customer experience. Zealogics partners with clients to understand their unique needs, delivering tailored solutions to achieve their business goals.

IT consulting • Systems Implementation • IT & Engineering Staffing • Mechanical Engineering • Electronics Engineering

501 - 1000 employees

🏢 Enterprise

☁️ SaaS

🤖 Artificial Intelligence

📋 Description

• Sr Azure Data Engineer • Remote • Contracted

🎯 Requirements

• Able to participate in business discussions and assist gathering data requirements. • Good analytical and problem-solving skills to help address data challenges. • Proficiency in writing complex SQL queries for data extraction, transformation, and analysis. • Knowledge of SQL functions, joins, subqueries, and performance tuning. • Able to navigate source systems with minimal guidance to understand how data is related and use like data profiling to gain a better understanding of the data. • Hands on experience with PySQL/Pyspark etc. • Hands on Experience in creating and managing data pipelines using Azure Data Factory. • Understanding of data integration, transformation, and workflow orchestration in Azure environments. • Knowledge of data engineering workflows and best practices in Databricks. • Able to understand existing templates and patterns for development. • Hands on experience with Unity Catalog and Databricks workflow. • Proficiency in using Git for version control and collaboration in data projects. • Ability to work effectively in a team environment, especially in agile or collaborative settings. • Clear and effective communication skills to articulate findings and recommendations for other team members. • Ability to document processes, workflows, and data analysis results effectively. • Willingness to learn new tools, technologies, and techniques as the field of data analytics evolves. • Being adaptable to changing project requirements and priorities.