Data Engineer
Data Engineer
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Job Description
A Data Analytics and Platform team within the Institutional Securities Technology division is seeking a collaborative handson developer to build bestinclass solutions for Data APIs Data Governance Data Quality Security & Privacy and Architecture. This role offers a unique opportunity to work in a stateoftheart modern data stack using opensource technologies aligned with our cloud strategy. We are looking for a proficient developer who is excited about innovation with a proven track record of delivery.
Roles and responsibilities include:
- You will work closely with quants and traders across multiple trading desks to design develop deploy and support the innovative data science environment
- Design widely used and flexible APIs to our core data and functionality
- Analyze and optimize performance of large data workloads using compute clusters
- Stay up to date with emerging trends and tools in the data & analytics domain
- Provide support and design advice to users of the crossasset platform
- Work closely with strategists and other stakeholders to help move their financial assets valuation models and data pipelines to the platform
- Efficient Communication across regions and functions
- At least 3 years relevant experience would generally be expected to find the skills required for this role
What were looking for: we have a number of roles available for a range of technologists at different experience levels to join the team who will need
- Excellent problem solving and code development skills
- Ability and interest to research learn and implement new Data and Analytics technologies and paradigms
- Enterprise level software development practices
- Strong oral and written communication skills
- Strong team working ability in local and global teams
- Passion for continuous improvement both personally and as a team
Skills that will help you in the role:
- Established experience with Python and Python ecosystem.
- Experience with performance optimization concurrent programming and microservices design.
- Good knowledge of data processing libraries and stacks (Polars Pandas Numpy Dask Spark) SQL/NoSQL (Mongo)Knowledge of ETL and streaming pub/sub platforms (Kafka)Knowledge of SDLC management tools (Git Jenkins Github docker Kubernetes Autosys) apps observability libraries (OpenTelemetry) and monitoring tools (Grafana Loki Tempo Prometheus).
- Exposure to grid distributed applications (optional)
- Exposure to KDB or other timeseries database technologies (optional)
- Exposure to Cloud technologies (optional)
- Exposure to Risk Management systems and a wide range of Financial Instruments (optional)
Employment Type
Full Time
