ABOUT THE ROLE
We are seeking a highly motivated Senior Data Engineer to join our Private Markets Data Team. This role will be responsible for the design, implementation, and maintenance of data engineering systems and governance processes, while contributing to the development of next-generation data solutions.
The ideal candidate is a well-rounded technologist with strong data engineering skills, hands-on programming experience, and a passion for building scalable, high-performance data systems. You should be comfortable working in a fast-paced environment, collaborating with cross-functional teams, and communicating complex technical concepts clearly to both technical and non-technical audiences.
This position offers the opportunity to work closely with data product managers, business analysts, and business stakeholders, gaining exposure to the investment management process and contributing to systems that provide a competitive edge to our investment teams.
RESPONSIBILITIES INCLUDE
- Design, develop, and maintain on-premises and cloud-based data ingestion and processing pipelines.
- Administer and extend data engineering tools including Airflow, DBT Cloud, Snowflake, and Python.
- Support and enhance the Data Governance process.
- Develop production-quality code and data solutions supporting key business initiatives.
- Conduct architecture and code reviews to ensure security, scalability, and quality across deliverables.
- Collaborate with cloud migration, information security, and business analysis teams to design and deploy new applications and migrate existing systems to Airflow and cloud-native technologies.
- Provide technical leadership and mentorship to onshore and offshore team members.
- Define and execute on a technical roadmap, identifying opportunities to improve processes, efficiency, and data quality.
- Optimize data pipeline performance and improve overall runtime of jobs.
TECHNOLOGY EXPERIENCE
- Proven experience building and maintaining on-premises and cloud-based data solutions.
- Hands-on experience supporting SaaS, business-facing applications.
- Comfortable using large language models (e.g., Claude, ChatGPT) day-to-day for data analysis and automation; working knowledge of prompt engineering and agentic / workflow-automation frameworks.
- Familiarity with AI-assisted coding tools (Claude Code, OpenAI Codex, or AI-native IDEs such as Cursor or Windsurf) and with extending AI through the Model Context Protocol (MCP) and reusable skills is a plus.
- Exposure to vector databases and retrieval-augmented generation (RAG) pipelines (e.g., Pinecone, pgvector, or Snowflake Cortex Search) for LLM-powered applications is a plus.
- Experience working within cloud-native AWS serverless data and integration products.
- Experience with containerization and orchestration tools such as Docker and Kubernetes.
- Expertise in Python for data processing, automation, and production-grade development.
- Strong knowledge of SQL, data modeling, and data warehouse design (e.g., One Big Table, Kimball/star schema).
- Experience building, deploying, and optimizing Snowflake Cortex AI using best practices.
- Experience with deployment tools such as Terraform, GitHub Actions, and ECR.
- Experience with infrastructure monitoring and observability tools such as Datadog, Grafana, or Amazon CloudWatch.
- Understanding of Power BI, Tableau, or similar BI/reporting tools.
- Familiarity with data pipeline technologies and orchestration tools (e.g., Airflow, DBT Cloud).
- Experience with Snowflake, Redshift, BigQuery, or Athena.
- Familiarity with modern lakehouse table formats such as Delta Lake, Apache Iceberg, or Apache Hudi is a plus.
- Understanding of data governance, data quality, and metadata management frameworks.
- Hands-on experience with data quality/observability tooling (e.g., Great Expectations, Monte Carlo, or Soda) and data catalog/lineage platforms (e.g., Alation, Collibra, or Unity Catalog) is a plus.
- Exposure to streaming and real-time data processing tools such as Kafka, Flink, or Spark Streaming is a plus.
- Familiarity with web scraping, APIs, and data integration best practices.
- Experience working in an Agile development environment.
QUALIFICATIONS
- BS or MS in Computer Science, Engineering, or a related technical field.
- 7+ years of professional software or data engineering experience.
- Strong foundation in software design and architectural patterns.
- Excellent communication, analytical, and problem-solving skills.
- Proven ability to translate complex business requirements into scalable data solutions.
- Experience with Big Data and streaming technologies preferred.
- Demonstrated ownership mindset and ability to drive projects from concept to completion.
- Highly collaborative team player who thrives in a fast-paced, dynamic environment.
- Self-starter with a commitment to continuous learning and innovation.
Why Join Us
At Bain Capital, you’ll have the opportunity to work with cutting-edge technologies in a collaborative environment that values innovation and excellence. You’ll be part of a high-performing team that leverages data to drive strategic decisions and investment insights 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.
