Opensee provides instant big data analytics solutions to financial institutions. Our mission is to empower business users to autonomously exploit data at a scale and granularity never seen before in order to optimize risk management, trade execution, regulatory reporting and more.

Founded in 2015 by senior banking executives and big data technology experts, Opensee's commercial traction exploded in 2020 with deployment in several Tier 1 financial institutions on critical use cases. To sustain that growth, we doubled our headcount that same year and are now expanding in London, NYC and Singapore.

What’s in it for you ?
* Develop expertise in one of the most advanced solutions for risk aggregation
* Work in a dynamic environment where innovation and creativity are highly valued
* Benefit from a wealth of development opportunities as we constantly seek new talent to join us and support our growth

What are you going to do ? 
You will work for SaaS implementation projects and support the whole project team involving Solution engineers, Quantitative Research and R&D.
Within 2 client projects (1 production and 1 project), end users will need to leverage the Versioning features of the Opensee system to manage data around trade analytics.

Most of this data is coming from 3rd party data sources. An ETL is being implemented to extract, transform and load data into the Opensee platform. Front Office Support, IT and Data Management users from financial institutions must be able to work on the ingested data and improve it over time.
Because implementations consist of replacing systems, Opensee must put together a work process for the client, consistent with the features brought.

ETL involves data orchestration and possibly data modelling parts.  Based on new functionality being implemented, you will work on the Data Management process. 

State of the art around Data Quality for Financial Services should provide a baseline for the target data management process. Solution team already implemented generic quality dashboards using configurable data KPIs (Key Performance Indicators).
This internship will include :

* Building internal organisations materials  for managing SaaS data issues proactively from internal tools to ticket system

* Implementation of data quality checks within latest Web UI  in the Trade Analytics use case or Market Risk use case

* Evaluate Apache Nifi against Apache Airflow  over a few months in the context so that ETL can become a “common” Customer Success tool

Keywords: project management, implementation, client support, finance, big data,  database, data management, SaaS, KPIs, ETL

Interest: Looking for challenge and growth within a dynamic fintech company ? Like problem  solving  and making things truly happen ? Come talk to us.
Qualities: Great communication and negotiation skills; autonomy AND teamwork; creative, problem-solving mindset, proactive, troubleshooter
Prior experience: Software development, implementation or support on client projects is a bonus.

* Client success oriented

* Big data / distributed databases / SQL , Apache Nifi, Apache Airflow, PostGreSQL, Clickhouse database, DBeaver, Python, DBT 
* Scripting / analysis / optimisation in the context of tera- or peta-scale data
* BI Data modelling, system integration and troubleshooting
* Financial knowledge (market risk, counterparty risk, liquidity, transaction analysis) is a bonus

Language skills: Fluent in English both written and verbal, French is a plus 

Working conditions 
* Position type: End-of-study internship (Engineer/ Master degree) or Gap-year
* Start: From September 2024 (flexible)
* Duration: 6 month for a full-time internship
* Localisation: Paris 17th
* Remuneration : competitive, profile based

How to apply
Send us your resume and a brief description of why you are interested in joining us, and we will come back to you very shortly!