Data Engineer

London, United Kingdom, United Kingdom

Explore the forefront of financial technology with SigTech, a leader in AI-driven quantitative backtesting software. For over a decade, we have been refining tools that transform complex data into actionable insights, enabling traders to optimise their strategies and achieve superior market performance. Our advanced platform, backed by comprehensive data from top-tier providers, ensures precise and reliable testing environments and is trusted by world leaders in the investing industry. At SigTech, you’ll join a team dedicated to pushing the boundaries of what’s possible in the trading world, using innovation to drive real results. If you're ready to contribute to pioneering solutions that shape the future of finance, we want to hear from you.

Find out more: SigTech

Requirements

  • Maintain, support and expand existing data pipelines using DBT, Snowflake and S3
  • Implement standardised data ingress/egress pipelines
  • Onboard new, disparate data sets, sourced from many and varied data vendors, covering all asset types and frequencies from daily to real-time
  • Liaise and work closely with our team of quant developers to make the data easy to use within the platform
  • Work with customers to enable them to onboard their own data onto our Platform
  • Create thorough operationalised documentation and support for all new pieces of work and retrospectively existing pieces of work
  • Full functional and unit testing of all deliveries

What you’ll need to succeed

  • A minimum of 3+ years experience in Data Engineering, including data integration, modelling, optimisation and data quality
  • Exceptional understanding of Python
  • Experience developing in the cloud (AWS preferred)
  • Solid understanding of libraries like Pandas and NumPy
  • Experience in data warehousing tools like Snowflake, Databricks, BigQuery
  • Familiar with AWS Step Functions, Airflow, Dagster, or other workflow orchestration tools
  • Commercial experience with performant database programming in SQL
  • Capability to solve complex technical issues, comprehending risks prior to the circumstance
  • Comfortable working in an agile environment, where features may change and evolve quickly

Great to haves

  • Prior experience in financial services, specifically capital markets or funds industry
  • Strong communication skills
  • Work experience in a start/scale-up

Benefits

  • Enjoy a generous 26 days of holiday, with the potential to earn up to 4 bonus days per year.
  • Indulge in up to 7 days of international work, allowing you to explore exciting destinations of your choice!
  • Work from home twice a week!
  • Take advantage of healthcare coverage that keeps you in good shape.
  • Access exclusive discounts on gym memberships.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Airflow AWS BigQuery Dagster Databricks Data pipelines Data quality Data Warehousing dbt Engineering Finance NumPy Pandas Pipelines Python Snowflake SQL Step Functions Testing

Perks/benefits: Flex vacation Startup environment

Region: Europe
Country: United Kingdom
Job stats:  9  4  0
Category: Engineering Jobs

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