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We are seeking an experienced Data Engineer to join our innovative team of data experts who are shaping the future of our finance data platform. This role will help us to build a robust data lake with clear semantics, effective governance, and a streamlined machine learning data pipeline that enables predictive modeling and optimizes financial resource allocation. The successful candidate should have expertise with data modeling, ETL, reporting, and data infrastructure, as well as experience working with large data sets. In addition, they will be enthusiastic about learning new technologies and able to implement solutions using them to provide new functionality. If you thrive in a fast-paced environment and enjoy the challenge of highly complex business contexts, we encourage you to apply. 

Typical Duties and Responsibilities

  • Design, implement, and support data lake infrastructure to provide secure access to large datasets
  • Gather requirements from customers and business stakeholders and deliver complete data solutions
  • Model data and metadata to support ad-hoc and pre-built reporting
  • Design, develop, and deploy scalable and observable backend microservices
  • Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards
  • Tune application and query performance using profiling tools and SQL
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets
  • Develop real-time data processing systems that turn unstructured data from various sources into factors that power the firm’s risk models
  • Develop a framework in the firm’s big data platform to simulate the impact of different strategies on the company’s portfolio
  • Monitor systems and applications to ensure optimal performance 
  • Analyze and improve our development workflow to support CI/CD principles and encourage the adoption of best practices
  • Identify strategies to automate and maintain scalable infrastructure
  • Prepare and maintain necessary documentation 
  • Participate in daily standups, team backlog grooming, and iteration retrospectives

Education

  • Bachelor’s degree in statistics, computer science, software engineering, or a related field

Required Skills and Experience

  • 2+ years of experience as a software, data, or DevOps engineer
  • Experience with microservices architecture, infrastructure as code, distributed services, and self-managed services
  • Experience with ETL development, SQL, and Unix/Linux scripting
  • Experience in big data technologies like Spark, Hive, and Presto
  • Experience with multiple programming languages, including Python
  • Experience with blockchain or cryptocurrency
  • Experience with distributed big data systems
  • Experience with cloud platforms and data bricks
  • Experience developing financial product methodologies for indices, reference rates, and exchange rates
  • Knowledge of data ingestion pipelines and massive data querying 
  • Knowledge of the technicalities of financial market data
  • Strong analytical, organizational, and problem-solving skills
  • Strong communication skills and the ability to explain concepts to both technical and non-technical staff

Preferred Qualifications

  • Experience with real-time stream processing frameworks like Kafka
  • Experience with data scraping