Senior Data Engineer at Baincapital in Boston, MA

Senior Data Engineer
Location: Boston
TITLE: Senior Data Engineer
DEPARTMENT: Capital Markets Group — Software Development, Data Analytics & Data Engineering
LOCATION: Boston, MA (Hybrid)
REPORTS: VP Development
BAIN CAPITAL OVERVIEW
With approximately $225 billion of assets under management, Bain Capital is one of the world’s leading private investment firms. We create lasting impact for our investors, teams, businesses, and the communities in which we live. Over four decades we have strategically grown our platform to focus on Private Equity, Growth & Venture, Capital Solutions, Credit, and Real Assets. Today, our team includes 1,985+ employees in 24 offices on four continents.
We partner differently to help people and companies embrace possibility and realize potential. Founded as a private partnership in 1984, we have fostered a culture of innovation, entrepreneurialism, and agility, empowering our people to define and own their career trajectories. Today, our partnership approach enables us to pursue strategic growth, build enduring relationships with a robust external network, and collaborate across our integrated platform to connect the deep and diverse expertise that unlocks breakthrough insights.
Our people are the heart of our advantage. Colleagues at all levels have a seat at the table as they tackle business challenges with a principal investor mindset. By asking incisive questions, respectfully challenging one another, and remaining intellectually agile, we work together to achieve exceptional outcomes.
For more information visit:Bain Capital
DESCRIPTION
The Capital Markets Group is building a modern, governed data platform that powers credit analytics, fund performance, and portfolio reporting. Our technology stack is Snowflake as the warehouse, dbt for transformation, Terraform for infrastructure-as-code, and Airflow for orchestration and python tooling. We model with Kimball dimensional and sound relational principles, and we hold a simple bar for everything we ship: never worse, always better.
We are seeking a Senior Data Engineer who not only writes excellent, tested, maintainable code, but who has genuinely incorporated agentic AI tooling — Claude, Codex, ChatGPT, Cursor, and similar — into how they design, build, review, and ship data products. This is not a “nice to have.” We expect engineers to use these tools fluently and responsibly to multiply their output without compromising correctness or governance. An AI-first way of working is the baseline for this role, not a bonus.
This is a hands-on engineering role with real proximity to the business. You will work directly with portfolio managers, traders, finance, operations and research analysts — gaining exposure to the investment management process and contributing to the systems that give our investment teams a competitive edge. The ideal candidate is a well-rounded technologist who is as comfortable defending a grain decision as they are pairing with an AI agent to refactor a pipeline.
You are a self-starter with an ownership mindset who thrives in a fast-paced, collaborative environment. You communicate complex technical concepts clearly to both technical and non-technical audiences, and you raise the bar for the people around you.
KEY RESPONSIBILITIES
AI-First Engineering & Innovation
Use agentic AI tools as part of your daily workflow — code generation, refactoring, test authoring, design review, documentation, and data-debugging — to deliver demonstrably faster, higher-quality work.
Help establish team standards for using AI tooling safely and effectively, with a clear point of view on where it helps, where it doesn’t, and how to keep its output correct, secure, and reviewable.
Stay at the forefront of rapidly evolving AI tooling and bring a grounded, practical perspective on where it creates genuine leverage in data engineering.
Champion adoption across the team, treating AI as a force multiplier rather than a shortcut — engineers remain accountable for correctness, security, and design.
Contribute to internal AI/agentic tooling where it advances the platform — MCP servers, retrieval, LLM-backed analytics assistants, or custom agents and skills.
Data Modeling & Platform Ownership
Design and build dimensional and relational data models in Snowflake that hold up under real reporting and analytics load — fact/dimension design, SCDs, conformed dimensions, and grain discipline.
Own end-to-end dbt pipelines: staging → intermediate → marts, with strong testing (schema, data, and custom tests), documentation, exposures, and CI.
Administer and extend the firm’s data governance, BI, and data-store ecosystem, including tools such as Atlan, Monte Carlo, Snowflake, and Power BI.
Build and enforce data quality, lineage, and observability so issues are caught before stakeholders ever see them.
Engineering Delivery & Infrastructure
Manage cloud infrastructure as code with Terraform — Snowflake resources (warehouses, roles, RBAC, databases/schemas) and supporting cloud services — through reviewable, repeatable, environment-promoted deployments.
Design, develop and maintain on-premises and cloud-based data ingestion and processing pipelines, and support the migration of existing systems to the cloud.
Conduct architecture and code reviews to ensure security, scalability, and quality across deliverables.
Partnership & Technical Leadership
Partner directly with analysts, PMs, and business stakeholders to turn ambiguous investment management questions into durable, well-modeled data assets.
Define and execute on a technical roadmap, identifying opportunities to improve processes, efficiency, and data quality.
Raise the bar in code review and design review; mentor onshore and offshore engineers on modeling, testing, and engineering craft.
Become the person analysts and stakeholders trust to make the data right.
WHAT MAKES YOU AN IDEAL CANDIDATE
You have built your career as a hands-on data engineer and you hold yourself to a high bar: every change leaves the codebase and the data better than it found them. You model deliberately, test rigorously, and automate your infrastructure — and you can defend a grain decision and explain why a model is right.
You see AI beyond the buzzword. You have genuinely incorporated agentic AI tooling into how you design, build, review, and ship — and you have a clear, pragmatic view of how to multiply your output with it while keeping the result correct, secure, and reviewable. You are accountable for what you ship, AI-assisted or not.
You communicate with clarity and confidence at all levels. You work comfortably alongside non-engineering stakeholders in a financial-services context, translating ambiguous business questions into scalable data solutions. You have a bias toward action and get things done without overcomplicating matters.
You are a highly collaborative team player and a self-starter with a commitment to continuous learning. You bring an ownership mindset and the ability to drive projects from concept to completion.
QUALIFICATIONS
5+ years in data engineering or a closely related software engineering role.
Hands-on, daily-use experience with agentic AI coding tools — Claude, Codex, ChatGPT, Cursor, or equivalent — with a clear point of view on where they help, where they don’t, and how to keep their output correct, secure, and reviewable.
Deep, demonstrable experience with Snowflake — performance, cost, RBAC/security, and warehouse/query design.
Strong dbt experience in a production environment — not just running models, but structuring projects, testing strategy, macros, and CI/CD.
Dimensional modeling (Kimball) and solid relational database fundamentals; strong SQL across the board, with comfort reasoning about query plans and data correctness.
Production Python with sound software engineering practice — OOP, testing, packaging, and version control.
Infrastructure-as-code with Terraform (or strong adjacent IaC experience with a clear path to Terraform).
Excellent communication, analytical, and problem-solving skills; proven ability to translate complex business requirements into scalable data solutions.
BS or MS in Computer Science, Engineering, or a related technical field.
Preferred / Nice to Have
Financial services, asset management, credit, or capital markets domain experience.
Experience building internal AI/agentic tooling — MCP servers, retrieval, LLM-backed analytics assistants, or custom agents and skills.
Orchestration tooling (Airflow, Dagster, dbt Cloud, or similar).
BI/reporting experience, Power BI especially.
CI/CD pipelines (GitHub Actions, Azure DevOps).
Data governance, lineage, and catalog tooling; exposure to streaming/real-time processing (Kafka, Flink, or Spark Streaming).
WHY THIS ROLE
You will work with cutting-edge technologies in a collaborative environment that values innovation, craft, and excellence, on a team that is deliberately building an AI-first engineering culture. For the right person, this is a chance to build something meaningful, work on genuinely hard problems, and grow alongside a high-performing team that leverages data to drive strategic decisions across global markets.
Compensation:
Expected Annual Base Salary $150,000 - $170,000.
Actual base salary will be determined by a wide range of factors including but not limited to role, function, level, experience, qualifications and geographic location. In addition to a competitive base salary, this position may be eligible for a discretionary annual bonus based upon factors such as individual impact, team and firm performance. Bain Capital offers a competitive benefits package designed to support employees’ health, financial security, family needs, and overall well-being.
Bain Capital is an equal opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.