Data Operations and Onboarding, Data Analyst
ROLE OVERVIEW
As a Data Analyst, you will collaborate with a global team of data engineers, data scientists, and content experts across BAM's key geographic locations. You will face off to PMs, Analysts and Data Scientists, to provide robust delivery of existing data feeds and onboarding of new data feeds.
This role is suitable for individuals who are inquisitive, passionate about technology and data, and eager to drive growth both personally and within a team. Your responsibilities will include:
- Actively monitor day-to-day data ingestion pipelines and quality check assertions and remediate issues in collaboration with platform engineers and data vendors. Provide transparent communication of issues and remediation actions to data consumers including PMs and data scientists.
- Actively engage with Front Office teams to deliver hands-on training and support for the BAM Platform, while also curating and creating comprehensive materials that facilitate user adoption and enhance their experience.
- Act as primary contact for onboarding of new data sets. Configure BAMs proprietary data ingestion systems and data quality engines to ensure new data is onboarded with highest level of quality and robustness.
- Ensure transparent reporting of onboarding status to all clients and execute a rigorous workflow for managing priorities and executing project work.
- Collaborate closely with the Data Platform engineering team to evolve BAMs tooling to improve data onboarding and day-to-day operations. Define innovative solutions to make onboarding a more productive and seamless operation.
- Contribute to BAM Data Standards to improve data quality, usefulness and accessibility.
QUALIFICATIONS & REQUIREMENTS
- We are seeking a talented team player who is eager to learn, comfortable working under pressure, and navigate uncertainties.
- The ideal candidate should have over 3 years of experience in technical support, implementation, and/or engineering roles, along with a Bachelor's or Master's degree in Mathematics, Computer Science, Engineering, Economics, or a related discipline.
- Proficiency in Python for data analysis and wrangling, as well as SQL and relational databases, is essential.
- You should also have a solid understanding of (or willing to learn) AWS, Git, and Airflow who can further expand responsibilities to areas like developing scripts to automate data processes, utilizing AWS for deploying and managing data solutions, using Git for version control, and implementing workflows using Airflow.
- Experience with financial data, particularly in time-series data and third-party data vendors, is preferred for quantitative and fundamental analysis.
- Experience using AI and LLM tools to automate tasks is preferred.
