Lead Software Engineer, Investment Analytics, VP

State Street

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Boston, MAQuincy, MA
Salary
$110,000–$188,750 / yr
Posted
1 day ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $195k
This role $149k
$96k most similar roles pay here $239k

This role pays less than 87% of similar roles. Most pay $167,525–$222,437 — the shaded band above. At the midpoint, this role pays about $149k versus about $195k for comparable roles.

Based on 240 similar postings.

Employer

About State Street

State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody

State Street currently has 206 open roles on FindRole.

Listed pay typically runs $120,000–$202,500 across 200 roles with salary data.

Most-posted roles

View all roles at State Street

At a glance

TL;DR · Lead Software Engineer, Investment Analytics, VP

Lead Software Engineer – Investment Analytics, VP - State Street Investment Management joins the Investment Analytics Application Development team to build and support systems that process, analyze, and deliver investment data for portfolio management, research, risk, and reporting. This role involves designing and optimizing scalable applications and data pipelines while translating complex financial concepts into high-quality solutions. The engineer will manage requirements analysis, solution design, and technical implementation within an Agile SDLC to address use cases like performance measurement, attribution, returns analysis, and benchmark comparisons. Key technologies include Python, PySpark, SQL, Databricks, and AWS. Candidates must possess expertise in financial data such as holdings, transactions, and market data. The role requires solving problems related to large-scale data processing, ensuring data quality, and maintaining robust workflows within an asset management environment using advanced Spark and SQL optimization techniques.

What you'll do

  • Design, build, and optimize scalable applications and data pipelines using Python, PySpark, and SQL on Databricks.
  • Translate complex financial concepts into technical solutions for portfolio management, risk, and reporting use cases.
  • Implement specialized financial analytics including performance measurement, attribution, returns analysis, and benchmark comparisons.
  • Optimize Spark and SQL workloads for scale using proper partitioning and Databricks best practices.
  • Lead the investigation and resolution of complex production issues through root-cause analysis and remediation.
  • Develop robust data workflows with a focus on data quality, transparency, and operational reliability.
  • Establish technical standards, documentation, and design reviews to improve development practices.

What we're looking for

  • Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
  • 10+ years of experience delivering technology solutions, preferably within asset management or financial services (preferred).
  • Advanced development skills in Python, PySpark, and advanced SQL.
  • Experience building solutions on Databricks and Apache Spark in a cloud environment like AWS (preferred).
  • Strong knowledge of financial data including returns, holdings, benchmarks, and market data.
  • Solid understanding of data warehousing and analytical data platform concepts.
  • Familiarity with BI and data visualization tools for reporting and insight delivery.
  • Experience leveraging AI-assisted development tools to improve productivity and code quality (preferred).

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