Senior Data Management Professional - Data Engineering - OTC Composites & Instruments
Posted Updated
Description
Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Our Team:
Our OTC Composite Pricing &Instruments team is seeking a Senior Data Engineer to help us drive our datasets forward. The team seeks to provide customers with transparency into OTC markets by generating market-reflective, proprietary rates across 200+ markets and and 100k+ instruments across Foreign Exchange, Interest Rate Derivatives, and Credit Default Swaps. We are responsible for maintaining and enhancing Bloomberg composites based on market rates from more than 2,000 third party pricing sources. OTC Composite pricing is a foundational service and an integral part of many workflows for our clients including trade execution, asset valuation, risk management, back office operations, and benchmarking.
What’s the Role?
As a Data Engineer on the OTC Composite pricing & instruments team, you’ll be relied upon to understand the client use case needs and resulting data quality requirements, specify the modeling needs of datasets and use existing techstack solutions for efficient data ingestion workflows and data pipelining. You will implement technical solutions using programming, machine learning, AI, and human-in-the-loop approaches to make sure our data is fit-for-purpose for our clients. You will work closely with our Engineering partners, our Data Product Manager as well as Product teams, so you need to be able to coordinate with multi-disciplinary and regional teams and have experience in project management and stakeholder engagement. You will need to be comfortable working with large datasets and you will need to demonstrate strong experience in data engineering.
We trust you to:
- Build and maintain robust and scalable ETL data pipelines to support the ingestion, transformation, and loading of vast amounts of data from sources using Bloomberg tech stack components such as Bloomberg Data Services, Dataflow recipes and Data Technologies Pipelines or equivalent tech stack such as Amazon S3, SQL, Python Pandas
- Analyze internal processes to find opportunities for improvement and process engineer efficient and innovative workflows using programmatic machine learning approaches
- Set up business rules and visualization to measure and ensure the accuracy, timeliness, and completeness of the FX dataset using Bloomberg tech stack components such as the Data Science Platform and QlikSense
- Collaborate with partners in creating data manipulation frameworks and establishing standard methodologies using Bloomberg's tech stack
- Apply your proven project management skills to ensure all technical projects are on track with right requirements
- Be responsive, resourceful, flexible and an excellent collaborator - Partner with our Product, Technology and Data Management Lab team to ensure consistent principles are leveraged, tools are fit for purpose, and results will be measurable
- Balance the best of technical and product knowledge to craft solutions for customers
- Experienced in managing and integrating large databases to develop analytical tools and automate manual tasks, providing valuable insights and efficiencies
- Keep up with the industry trends, standards, and innovation in the data quality domain
You'll need to have:
- 3 years of programming and scripting in a production environment (Python, Javascript, etc)
- 3 years of experience working with databases using SQL
- Experience working with extremely large data volumes
- Strong understanding of data warehousing methodologies, ETL processing and dimensional data modeling
- A bachelor’s degree or higher in Computer Science, Mathematics, or relevant data technology field, or degree-equivalent qualifications
- Experience in crafting and developing data quality metrics and reporting as a part of a bigger data architecture framework
- Exceptional problem-solving skills, numerical proficiency and high attention to detail
- Ability to work independently as well as in a distributed team environment
- Ability to optimally communicate and present concepts and methodologies to diverse audiences
- Familiarity with time series analytics and statistical methodologies
We'd Love to See:
- Data Management Association Certified Data Management Professional, Data Capability Assessment Model certification
- Demonstrable experience in Data Profiling/Analysis using tools such as Python, R, or SQL
- Knowledge of business intelligence reporting tools such as QlikSense, Power BI
- Familiarity with Iceberg and Trino solutions
- Knowledge of streaming technologies like Kafka
- Familiarity with client use cases of OTC composite pricing across currency and interest rates instruments