Software Engineering Lead – Investment Analytics, VP

Jobtailor; Boston (MA); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor seeks a senior data engineer to design, build, and optimize scalable data pipelines using Python, PySpark, and SQL on Databricks (AWS). The role partners with stakeholders across research, portfolio management, risk, and reporting to translate analytics needs into robust solutions.

You will implement financial analytics use cases like performance attribution and benchmark comparisons, contribute to agile development, and ensure data quality, reliability, and end-to-end solution

Qualifications

• 10+ years of delivering technology solutions in asset management or financial services.
• Bachelor's degree in CS/CE or equivalent practical experience.
• Strong written and verbal communication skills.
• Strong experience with financial data in asset management or capital markets.
• Advanced development skills in Python, PySpark, and SQL.
• Experience building solutions on Databricks / Spark in a cloud environment (AWS preferred).
• Solid understanding of data warehousing and analytic data platforms.
• Strong analytical and problem-solving skills with independence.

Responsibilities

• Design, build, and optimize scalable applications and data pipelines using Python, PySpark, and SQL on Databricks (AWS).
• Partner with business stakeholders to understand financial data, analytics requirements, and downstream usage across research, portfolio management, risk, and reporting.
• Implement solutions that support financial analytics use cases, including performance measurement, attribution, returns analysis, and benchmark comparisons.
• Participate in requirements analysis, solution design, and technical implementation following an Agile SDLC.
• Develop robust, maintainable data workflows with emphasis on data quality, transparency, and operational reliability.
• Optimize Spark and SQL workloads for scale and performance with proper partitioning and best practices.
• Own investigation and resolution of complex production issues, including root-cause analysis and remediation.
• Collaborate with application, data architecture, and infrastructure teams for end-to-end solutions.
• Contribute to standards, best practices, documentation, and design reviews.
• Stay current with emerging technologies and recommend improvements to tools and development practices.

Skills

Python

PySpark

SQL

Data Pipeline Development

Data Quality Assurance

Root-Cause Analysis

Agile SDLC

Data Warehousing

Analytical Data Platforms

Performance Measurement

Education

Bachelor's degree in Computer Science/Engineering or equivalent

Tools

Databricks

AWS

Apache Spark

Job description

• Design, build, and optimize scalable applications and data pipelines using Python, PySpark, and SQL on Databricks (AWS)
• Partner with business stakeholders to understand financial data, analytics requirements, and downstream usage across research, portfolio management, risk, and reporting
• Implement solutions that support financial analytics use cases, including (but not limited to) performance measurement, attribution, returns analysis, and benchmark comparisons
• Participate in requirements analysis, solution design, and technical implementation following an Agile SDLC
• Develop robust, maintainable data workflows with strong emphasis on data quality, transparency, and operational reliability
• Optimize Spark and SQL workloads for scale and performance using appropriate partitioning, query design, and Databricks best practices
• Own the investigation and resolution of complex production issues, including root-cause analysis and long-term remediation
• Collaborate with application, data architecture, and infrastructure teams to deliver end-to-end solutions
• Contribute to technical standards, best practices, documentation, and design reviews
• Remain current with emerging technologies and recommend improvements to tools, frameworks, and development practices

Requirements

• 10+ years of experience delivering technology solutions, preferably within asset management or financial services
• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience
• Strong written and verbal communication skills
• Strong experience working with financial data in an asset management or capital markets environment
• Advanced development skills in: Python, PySpark, and advanced SQL
• Experience building solutions on Databricks / Apache Spark in a cloud environment (AWS preferred)
• Solid understanding of data warehousing and analytical data platform concepts
• Strong analytical and problem-solving skills with the ability to work independently.

Core Competencies

Demonstrates expertise in designing and optimizing scalable applications and data pipelines using Python, PySpark, and SQL on Databricks, with a strong focus on financial data analytics and operational reliability. Proven ability to collaborate with stakeholders and deliver end-to-end solutions in an Agile environment.

Highest-signal resume keywords

• Python Development
• PySpark Application Development
• SQL Optimization
• Databricks Solutions Architecture
• Financial Data Analytics

ATS Optimization Keywords

Hard Skills

• Python
• PySpark
• SQL
• Data Pipeline Development
• Data Quality Assurance
• Root-Cause Analysis
• Agile SDLC
• Data Warehousing
• Analytical Data Platforms
• Performance Measurement

Soft Skills

• Strong Communication Skills
• Analytical Problem-Solving
• Collaboration

Industry Keywords

• Asset Management
• Financial Services
• Capital Markets
• Performance Attribution
• Benchmark Comparisons

Tools & Technologies

• Databricks
• AWS
• Apache Spark