Job
Description
Role Overview: As a Data Engineer at Guidehouse, you will be responsible for leading and executing data engineering projects from start to finish, ensuring timely delivery and high quality. You will collaborate with cross-functional teams to gather and define data requirements, implement data quality and security practices, and manage cloud-based data platforms. Additionally, you will develop and maintain Python/PySpark libraries for data ingestion, processing, and integration with internal and external data sources. Your role will involve designing scalable data pipelines, mentoring junior data engineers, and evaluating new technologies to improve data infrastructure. Key Responsibilities: - Lead and execute data engineering projects, ensuring timely delivery and high quality - Build and optimize data architectures for operational and analytical purposes - Collaborate with cross-functional teams to gather and define data requirements - Implement data quality, data governance, and data security practices - Manage and optimize cloud-based data platforms (Azure, AWS) - Develop and maintain Python/PySpark libraries for data ingestion, processing, and integration - Design and optimize scalable data pipelines using Azure Data Factory and Spark (Databricks) - Work with stakeholders to assist with data-related technical issues and support data infrastructure needs - Develop frameworks for data ingestion, transformation, and validation - Mentor junior data engineers and guide best practices in data engineering - Evaluate and integrate new technologies and tools to improve data infrastructure - Ensure compliance with data privacy regulations - Monitor performance and troubleshoot issues across the data ecosystem Qualifications Required: - Bachelor's or master's degree in computer science, Information Systems, Statistics, Math, Engineering, or related discipline - Minimum 10+ years of solid hands-on experience in data engineering and cloud services - Experience in leading and mentoring team members - Good experience in Azure Data Factory (ADF), Databricks, Python, and PySpark - Experience in modern data storage concepts such as data lake and lake house - Experience in other cloud services (AWS) and data processing technologies - Ability to enhance, develop, and resolve defects in ETL processes using cloud services - Experience handling large volumes of incoming data from various sources in different formats - Experience with programming languages such as Java, .Net - Experience with software development methodologies and version control tools - Highly motivated, strong problem solver, self-starter, and fast learner with demonstrated analytic and quantitative skills - Good communication skills Additional Company Details: Guidehouse offers a comprehensive total rewards package that includes competitive compensation and a flexible benefits package. Guidehouse is an Equal Opportunity Employer and considers qualified applicants with criminal histories in accordance with applicable law. If accommodations are needed during the application process, applicants can contact Guidehouse Recruiting for assistance. Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process. Applicants are advised to report any unauthorized requests for money related to job opportunities at Guidehouse. Role Overview: As a Data Engineer at Guidehouse, you will be responsible for leading and executing data engineering projects from start to finish, ensuring timely delivery and high quality. You will collaborate with cross-functional teams to gather and define data requirements, implement data quality and security practices, and manage cloud-based data platforms. Additionally, you will develop and maintain Python/PySpark libraries for data ingestion, processing, and integration with internal and external data sources. Your role will involve designing scalable data pipelines, mentoring junior data engineers, and evaluating new technologies to improve data infrastructure. Key Responsibilities: - Lead and execute data engineering projects, ensuring timely delivery and high quality - Build and optimize data architectures for operational and analytical purposes - Collaborate with cross-functional teams to gather and define data requirements - Implement data quality, data governance, and data security practices - Manage and optimize cloud-based data platforms (Azure, AWS) - Develop and maintain Python/PySpark libraries for data ingestion, processing, and integration - Design and optimize scalable data pipelines using Azure Data Factory and Spark (Databricks) - Work with stakeholders to assist with data-related technical issues and support data infrastructure needs - Develop frameworks for data ingestion, transformation, and validation - Mentor junior data engineers and guide best practices in data engineering - Evaluate and integrate new technologies and tools to improve data infrastructure - Ensure compliance
