Data Engineer

Macro Hive; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Macro Hive (BGC Group) seeks a Data Engineer for the Markets & AI Data Platform in London to build the data backbone for AI, quant models and client tools. You will transform messy data into clean, model-ready datasets and support end-to-end data flows.

You will own data pipelines for market, economic, research, news, internal and Fenics/BGC data, manage data architecture tiers, metadata, APIs and dashboards, and maintain data quality and lineage.

Qualifications

• Strong Python and SQL must-have expertise.
• Production ETL/ELT experience required.
• Cloud data stack: Azure, Databricks, Delta Lake, Snowflake or similar.
• Time-series or complex-data experience essential.
• Data quality, monitoring and audit awareness required.
• Ability to turn messy data into clean model-ready datasets.

Responsibilities

• Own data pipelines for market, economic, research, news and internal data.
• Maintain bronze/silver/gold data architecture and data lineage.

Skills

Python

SQL

ETL/ELT

Time-series data

Data quality

Tools

Azure

Databricks

Delta Lake

Snowflake

kdb+

Job description

Macro Hive (BGC Group) is a leading independent provider of global macro strategy. We combine best-in-class human and artificial intelligence to provide institutional investors with market-leading investment opportunities. Our experts leverage large language models, such as those that power chatbots like ChatGPT, to develop innovative, data-driven solutions to complex financial problems and to build state-of-the-art models in search of alpha signals across asset classes.

Data Engineer — Markets & AI Data Platform

Mission:

Build the data backbone for AI, quant models and client tools.

Owns:

• Market, economic, research, news, internal and Fenics/BGC data pipelines
• Bronze/silver/gold data architecture
• Instrument, ticker, country, client, source and theme metadata
• APIs/tables for agents, dashboards and quant models
• Data lineage, entitlements, permissions and monitoring

Must have:

• Strong Python and SQL
• Production ETL/ELT experience
• Cloud data stack: Azure, Databricks, Delta Lake, Snowflake or similar
• Time-series or complex-data experience
• Data quality, monitoring and audit awareness
• Ability to turn messy data into clean model-ready datasets

Nice to have

• Experience with ticker level data using for example kdb+