Senior Data Engineer - Python, AWS, CI/CD

Founded in 2013 by Vinesh Jha, ExtractAlpha is an independent research firm dedicated to providing unique, actionable alpha signals to institutional investors. We apply our extensive experience in quantitative analysis and the design of investment analytics products to interesting new data sets. Our rigorously built quantitative signals help our institutional investor clients gain a measurable edge over their competitors.

We partner with some of the world’s leading financial and fintech data firms to identify investment value in big datasets, and help investors profit from unique sources of information.

ExtractAlpha is a DaaS (Data as a Service) research firm dedicated to providing unique, actionable alpha signals to investors. We apply our extensive experience in quantitative analysis and the design of investment analytics products to creating data sets. Our quantitative models are designed for investors to gain a measurable edge over their competitors. We also partner with top FinTech data firms to identify investment value in their data sets and help investors profit from these unique new sources of information. Position Overview: As a Senior Data Engineer, you will be responsible for building and optimizing robust data pipelines, focusing on ETL processes, and supporting the architecture that powers our data-driven products. This is a hands-on role that requires a deep understanding of data engineering, cloud technologies (primarily AWS), and modern software development practices. You will work closely with our financial researchers, analysts, and sales to ensure high data quality, availability, and performance.

•Design, develop, and maintain scalable ETL pipelines for large-scale data processing. •Build and optimize data workflows using Airflow and Python. •Manage and integrate data from diverse sources using 3rd party APIs, SQL, and AWS services. •Collaborate with cross-functional teams to ensure data architecture aligns with business objectives. •Ensure data pipelines and infrastructure are highly reliable, maintainable, and scalable. •Work on performance tuning and optimization of data processing systems. •Implement and maintain CI/CD pipelines for seamless deployment and automation. •Create monitoring, logging, and observability systems to track and optimize data systems. •Troubleshoot, debug, and optimize data workflows to ensure data integrity and accuracy. •Stay up to date with the latest technologies and trends in data engineering and cloud computing.

Must-Have Requirements: •5+ years of experience as a Data Engineer with a focus on ETL processes, Python, Airflow, SQL, and AWS. •Recent experience working in a small team or as the only dedicated Data Engineer. •Proven expertise with CI/CD tools and automation for seamless data pipeline delivery. •Strong problem-solving skills and ability to work autonomously. •Experience with building and maintaining high-performing, reliable, and scalable data architectures. Nice-to-Have Skills: •Expertise with AWS services such as MWAA, Glue, Lambda, EventBridge, Fargate, RDS, Postgres. •Familiarity with monitoring, logging, and observability frameworks in the context of data pipelines. •Hands-on experience with cloud data warehouses (e.g., Redshift, Snowflake). •Familiarity with containerized environments (e.g., Docker, Kubernetes).