We are seeking a skilled Data Engineer to design, develop, and maintain robust data solutions. This role involves creating efficient data pipelines, ensuring data integrity, and implementing ETL processes for seamless data migration and deployment across various systems. You will be instrumental in building and maintaining the infrastructure that powers data processing and analysis, collaborating with stakeholders to ensure data availability and usability for business intelligence and analytics.

This position offers an exciting opportunity to integrate and unify diverse database systems within a dynamic ecosystem. You will work in cross-functional teams, translating complex data needs into actionable solutions and communicating effectively with both technical and non-technical audiences. Your contributions will be vital in developing and optimizing data architectures to meet evolving analytical demands.

Key responsibilities include integrating diverse database systems by building and maintaining scalable ETL pipelines to handle large data volumes, ensuring adherence to data governance and security policies. You will collaborate with data scientists, analysts, and business partners, delivering tailored solutions and clear communication. Develop and refine data architectures and transformation technologies to support analytical requirements.

Manage and optimize databases for performance, scalability, and availability. Integrate data from various sources, including APIs, cloud platforms, and internal systems. Proactively identify and resolve data processing bottlenecks to enhance database and pipeline performance. Implement comprehensive monitoring and logging solutions to ensure data reliability and quality.

Ideal candidates possess a strong foundation in Data Engineering principles and a minimum of 2-5 years of relevant experience, with a range up to 8 years considered. Essential technical skills include proficiency in Python, SQL, and experience with data warehousing and modeling. A solid understanding of AWS Services is also a must.

Proficiency in database management systems (SQL, NoSQL), big data technologies (Hadoop, PySpark), and data warehousing solutions (Snowflake, Redshift, BigQuery) is highly valued. Familiarity with DevOps tools like Gitlab, Docker, and Kubernetes is beneficial. Strong analytical skills, a proactive problem-solving approach, and the ability to work both independently and collaboratively are crucial. Experience coaching junior team members is a plus. Fifteen years of full-time education is required.