Data Engineer

As a Data Engineer, you will play a crucial role in designing and developing data-driven solutions for our clients. Your expertise in data exploration, Python, and SQL will be utilized to create efficient and scalable data pipelines. With a focus on Azure, you will leverage its data products and services to build robust and secure data architectures. Your role is key in ensuring data integrity, performance, and governance, while also contributing to the overall success of our data-centric projects.
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
8+ years of experience in data engineering or a similar role, with a strong focus on Azure technologies.
Proficiency in Python for ETL development and data wrangling, and experience with Databricks.
Excellent knowledge of SQL programming, including stored procedures and functions.
Experience with data warehouse modeling methodologies, such as Kimball or Data Vault 2.0.
Familiarity with Azure Data Factory, Databricks, Synapse Analytics, and ADLS Gen2 is a must.
Strong analytical and problem-solving skills, with the ability to work independently and manage multiple tasks.
Excellent communication skills, both written and verbal, to effectively collaborate with cross-functional teams.
A proactive and self-motivated attitude, with a passion for data engineering and a desire to stay updated with industry trends.
Experience with source control (e.g., Git) and ADO is preferred.
Design and develop data pipelines and architectures using Azure Data Factory, Databricks, and Synapse Analytics.
Implement data warehouse modeling methodologies, including Kimball and Data Vault 2.0, to ensure efficient data storage and retrieval.
Write automated tests for data pipelines to maintain data integrity and quality.
Utilize Python and T-SQL for ETL development and data wrangling, especially in Databricks.
Collaborate with cross-functional teams to understand business requirements and translate them into technical data solutions.
Ensure data governance practices are followed, including the use of Azure Purview or similar tools.
Stay updated with the latest data engineering technologies and best practices, and contribute to the continuous improvement of our data practices.
Document and communicate data-related processes and decisions to stakeholders.
Troubleshoot and resolve data-related issues, and provide timely support to the team.
Actively participate in code reviews and provide constructive feedback to ensure high-quality data engineering work.