Senior Technical Manager - Investment Data & Platform Engineering
Overview
We are seeking a hands-on Senior Data Engineer with deep expertise in financial datasets, time-series processing, and production-grade ETL pipelines. This role is ideal for someone who has spent the last several years building, maintaining, and scaling data pipelines used by investment, risk, and analytics teams-not a product manager, quant researcher, strategist, or people manager.
You will operate as a senior individual contributor who can independently deliver high‑quality engineering output while providing light technical guidance to nearby teams.
What You'll Do
- Own, build, and improve Python + SQL-based ETL pipelines supporting risk, performance, and portfolio analytics.
- Develop and maintain PostgreSQL schemas, queries, stored procedures, and data models for investment datasets.
- Build and optimize Parquet‑based pipelines and columnar data workflows supporting scalable analytics.
- Ingest, clean, validate, and transform large‑scale financial datasets (market data, pricing, risk factors, benchmarks, time‑series).
- Troubleshoot production workflows, ensure data quality, and implement robust monitoring & documentation.
- Partner directly with portfolio analytics, risk, and research teams to understand data requirements and deliver reliable solutions.
- Contribute as a technical lead (not people manager) by setting engineering standards and improving coding, documentation, and workflow practices.
What We're Looking For
Must-Have Technical Skills
- Python for production ETL (pandas, numpy, data engineering workflows).
- Experience in people management
- Expert-level PostgreSQL and SQL development.
- Experience building Parquet, columnar, or lakehouse‑style pipelines.
- Strong track record processing financial data:
- Market data
- Risk/portfolio analytics data
- Exposures & factor models
- Pricing, benchmarks, time-series
- Ability to design, document, and own engineering solutions with minimal oversight.
- Experience supporting production environments in investment or risk‑focused settings.
Nice-to-Have
- Experience with workflow orchestration (Airflow, Prefect, Dagster)
- Familiarity with Bloomberg, FactSet, Morningstar, or vendor data APIs
- Prior work supporting PMs, quants, or risk teams
- Knowledge of time-series modelling or analytics workflows (not required)
Who You Are
- A data engineer first - not a quant PM, BA, product manager, or strategist.
- Someone who enjoys building pipelines, writing code, debugging workflows, and working close to the data.
- Comfortable partnering with investment and analytics teams but remaining squarely in the engineering lane.
- Able to step into a fast-moving environment and deliver immediately.
Why This Role Matters
This team needs someone who can solve engineering problems on day one - not someone who supervises others or designs high-level strategy. Your work will be core to delivering the firm's analytics, risk, and portfolio data capabilities.
FAQs
Congratulations, we understand that taking the time to apply is a big step. When you apply, your details go directly to the consultant who is sourcing talent. Due to demand, we may not get back to all applicants that have applied. However, we always keep your CV and details on file so when we see similar roles or see skillsets that drive growth in organisations, we will always reach out to discuss opportunities.
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