Senior Data Engineer

Propelus simplifies workforce compliance management across healthcare. The Data Engineer plays a crucial role in building and maintaining the data infrastructure that supports the company's data strategy, focusing on developing data pipelines and ensuring data quality.

Responsibilities:

• Participate in the design, development, and maintenance of data pipelines using ETL/ELT processes to ingest, transform, and load data from various sources into the data warehouse
• Implement and maintain data quality checks and validation processes to ensure data accuracy and reliability
• Collaborate with data scientists and analysts to understand their data requirements and provide solutions to meet their analytical needs
• Contribute to the development and maintenance of data models, schemas, and dictionaries to ensure data consistency and usability
• Monitor data pipeline performance and troubleshoot data-related issues in a timely manner
• Assist in the evaluation and implementation of new data technologies and tools
• Develop and maintain documentation for data pipelines, processes, and data models
• Contribute to the development of data governance policies and procedures
• Participate in code reviews and knowledge sharing sessions with other data engineers
• Support the migration of existing data pipelines to more scalable and efficient solutions

Requirements:

• Bachelor's degree in Computer Science, Data Science, or a related field
• 4+ years of experience in data engineering or a similar role
• Proficiency in at least one programming language such as Python or Java
• Understanding of data warehousing concepts, modeling and methodologies
• Proficiency in SQL and experience with database management systems (e.g., MySQL, PostgreSQL, Oracle)
• Experience with optimizing complex queries
• Strong proficiency in using Git for version control and collaboration on codebase
• Experience with NoSQL databases (e.g., MongoDB)
• Familiarity with cloud-based data platforms (e.g., AWS, Azure, GCP)
• Experience with ETL/ELT tools such as Apache Airflow or similar
• Ability to work collaboratively with teams across data science, business intelligence, and software engineering to deliver high-quality data solutions
• Solid understanding of the importance of data validation and the basics of ensuring data quality (e.g., checking for duplicates, missing values, or incorrect data formats)
• Basic knowledge of data modeling techniques
• Strong analytical and problem-solving skills
• Excellent communication skills