propelus - Senior Data Engineer

Remote - USA3w ago

Remote Senior NA Life Insurance Health Insurance Senior Data Engineer Java Git Python Data Quality PostgreSQL MySQL SQL Oracle MongoDB NoSQL AWS Azure GCP Airflow Business Intelligence Documentation Data Governance

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. • BENEFITS AND PERKS FOR PROPELUS EMPLOYEES INCLUDE BUT ARE NOT LIMITED TO: • Awarded one of BuiltIn's 2025 Best Places to Work https://builtin.com/awards/colorado/2025/best-midsize-places-to-work and honored as a Silver Stevie® Award Winner in the 2025 Stevie Awards For Great Employers https://propelus.com/article/silver-stevie-award-2025-great-employers/. • Professional development allowance to help you grow in the ways that mean the most to you. • Flexibility for balancing work with the rest of life and ample PTO, including paid time off for volunteering, your birthday, and becoming a new parent. • Check us out for yourself at our careers page https://propelus.com/careers/ or our Propelus culture https://instagram.com/propelusculture/?img_index=1 Instagram accounts. • For US Employees: • 401K with company matching, as well as financial planning education and resources. • Employees can choose from HSA, FSA, and traditional insurance options for medical, dental, and vision coverage for themselves and dependents. • Lifestyle Spending Account (LSA): We support personal well-being by offering an annual lifestyle spending account that you can use for what matters most to you—whether it’s a gym membership, a meditation app, WFH equipment, or fresh produce delivered to your door. • For LATAM Employees: • Your health is our top priority! We cover 100% of your health insurance premiums. Our plans include national and international coverage, so you're protected no matter where you are. • Propelus Flex Club: Our flexible benefits platform gives you monthly points to redeem on what you need most. Plus, you'll get access to exclusive discounts just for being part of our team. • We've got you covered with a life insurance policy, paid 100% by the company. You can also add your beneficiaries at an exclusive, discounted rate.

Responsibilities

• 1. 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. • 2. Implement and maintain data quality checks and validation processes to ensure data accuracy and reliability. • 3. Collaborate with data scientists and analysts to understand their data requirements and provide solutions to meet their analytical needs. • 4. Contribute to the development and maintenance of data models, schemas, and dictionaries to ensure data consistency and usability. • 5. Monitor data pipeline performance and troubleshoot data-related issues in a timely manner. • 6. Assist in the evaluation and implementation of new data technologies and tools. • 7. Develop and maintain documentation for data pipelines, processes, and data models. • 8. Contribute to the development of data governance policies and procedures. • 9. Participate in code reviews and knowledge sharing sessions with other data engineers. • 10. Support the migration of existing data pipelines to more scalable and efficient solutions.