Lead Data Engineer
Access SystemsInternship
Mid-level (3 to 4 years), Senior (5 to 8 years)
The ideal candidate possesses strong Python proficiency in a production environment, with experience in cloud platforms like AWS (Glue, Redshift, S3). They should have hands-on experience with ETL/ELT pipelines for batch and real-time data, familiarity with big data tools such as Spark or Hive, and working knowledge of Terraform, Kubernetes, and CI/CD. Excellent communication and collaboration skills are essential, along with experience in orchestration tools like Prefect or Airflow, exposure to modern data workflows, and an understanding of data quality monitoring frameworks.
This role involves designing, building, and maintaining data pipelines to support analytics and product features, owning data integrations, and ensuring data quality and modeling. The Senior Data Scientist will collaborate with data scientists, analysts, and engineers to provide data in the correct format, leverage cloud infrastructure for scalable solutions, and troubleshoot data issues to improve pipeline performance.
Cloud-based platform for mortgage operations
Polly.io offers a platform designed to improve the mortgage industry by making operations more efficient for lenders. The platform is cloud-based, which means it uses internet technology to provide secure and scalable services. This allows lenders to access advanced tools for data analysis and machine learning, helping them to price loans and manage loan locks more accurately and quickly than traditional methods. Polly.io also features a Loan Trading Exchange that connects buyers and sellers of mortgage loans, making the process more transparent and efficient. By providing real-time analytics and market insights, Polly.io helps lenders make better decisions. The goal of Polly.io is to empower lenders of all sizes to enhance their productivity and profitability through its comprehensive suite of tools.