Senior Data Engineer

Cerberus Capital Management; New York (NY); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

High-impact team environment

Global exposure and travel opportunities

Collaborative and innovative culture

Job summary

A leading private investment firm in New York is seeking a Senior Data Engineer to build and maintain data platforms for investment operations. The successful candidate will design scalable data architectures and pipelines, utilizing tools like Azure and Snowflake. Collaboration with data scientists and analysts, along with strong Python and SQL skills, are essential. This full-time position is based in-office, fostering teamwork and innovation while offering opportunities for global exposure and travel.

Qualifications

• Hands-on experience in data engineering and pipeline development.
• Proficiency in data modeling, governance, and security.
• Experience optimizing data storage and processing.

Responsibilities

• Design and maintain scalable data pipelines and architectures.
• Optimize performance in Azure environments.
• Collaborate with teams to ensure seamless data integration.

Skills

Python expertise

Strong technical foundation in production environments

Cloud platforms experience (Azure preferred)

Data warehousing expertise with Snowflake

Production experience with Apache Airflow

SQL databases (PostgreSQL, SQL Server)

Communication and problem-solving skills

Education

Bachelor's or Master's degree in Computer Science or Engineering

Relevant certification from Azure, AWS, GCP, Snowflake, dbt

Tools

Snowflake

Azure DevOps

Git

Terraform

Job description

Functional / Industry Experience: Sr. Data Engineer (5 – 10 years)

Position Type (Core/Consultant/BOD): Core

Time Commitment: Full-Time

Summary

We are looking to expand our Data Engineering team to build modern, scalable data platforms for our internal investment desks and portfolio companies. You will contribute to the firm’s objectives by delivering rapid and reliable data solutions that unlock value for Cerberus desks, portfolio companies, and other businesses. You’ll do this by designing and implementing robust data architectures, pipelines, and workflows that enable advanced analytics and AI applications. You may also support initiatives such as due diligence and pricing analyses by ensuring high-quality, timely data availability.

Responsibilities

• Design, build, and maintain scalable, cloud-based data pipelines and architectures to support advanced analytics and machine learning initiatives.
• Develop robust ELT/ELT workflows using tools like Snowflake, MS Fabric, dbt, ADF, Airflow, and relational DBs such as SQL Server and PostgreSQL to transform raw data into high-quality, analytics‑ready datasets.
• Collaborate with data scientists, analysts, and software engineers to ensure seamless data integration and availability for predictive modeling and business intelligence.
• Optimize data storage and processing in Azure environments for performance, reliability, and cost‑efficiency.
• Implement best practices for data modeling, governance, and security across all platforms.
• Troubleshoot and enhance existing pipelines to improve scalability and resilience.

Sample Projects You Work On

Financial Asset Management Pipeline: Build and manage data ingestion from third‑party APIs, model data using dbt, and support machine learning workflows for asset pricing and prediction using Azure ML Studio. This includes ELT processes, data modeling, running predictions, and storing outputs for downstream analytics.

Your Experience

We’re a small, high‑impact team with a broad remit and diverse technical backgrounds. We don’t expect any single candidate to check every box below – if your experience overlaps strongly with what we do and you’re excited to apply your skills in a fast‑moving, real‑world environment, we’d love to hear from you.

• Strong technical foundation: Degree in a STEM field (or equivalent experience) with hands‑on experience in production environments, emphasizing performance optimization and code quality.
• Python expertise: Advanced proficiency in Python for data engineering, data wrangling and pipeline development.
• Cloud Platforms: Hands‑on experience working with Azure. AWS experience is considered, however Azure exposure is preferred.
• Data Warehousing: Proven expertise with Snowflake – schema design, performance tuning, data ingestion, and security.
• Workflow Orchestration: Production experience with Apache Airflow (Prefect, Dagster or similar), including authoring DAGs, scheduling workloads and monitoring pipeline execution.
• Data Modeling: Strong theoretical and practical understanding of relational and dimensional modeling. Proficient in dbt, including writing modular SQL transformations, building data models, and maintaining dbt projects.
• SQL Databases: Extensive experience with PostgreSQL, SQL Server (or similar), including schema design, optimization, and complex query development.
• Version Control and CI/CD: Familiarity with Git‑based workflows and continuous integration / deployment practices (experience with Azure DevOps or Github Actions) to ensure seamless code integration and deployment processes.
• Communication and problem‑solving skills: Ability to articulate complex technical concepts to technical and non‑technical stakeholders alike. Excellent problem‑solving skills with a strong analytical mindset.
• Infrastructure as Code (Nice to have): Production experience with declarative infrastructure definition – e.g. Terraform, Pulumi or similar.

Professional Experience & Education

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Relevant certification from Azure, AWS, GCP, IBM, Snowflake, dbt.

Other Requirements

• Cross industry exposure and experience preferred.
• 5 days a week in‑office: We believe in the power of in‑person collaboration to drive innovation, mentorship, and velocity. This role is based in our office five days a week – ideal for those who thrive in high‑energy, team‑centric environments.
• Global exposure: Be ready to travel! This role offers occasional cross‑continental and international travel opportunities, giving you the chance to engage with global teams, portfolio companies, and cutting‑edge tech initiatives around the world.

Work Authorization

We are unable to sponsor or transfer employment visas at this time.

Company Description

Established in 1992, Cerberus Capital Management, L.P., together with its affiliates, is one of the world’s leading private investment firms. Through its team of investment and operations professionals, Cerberus specializes in providing both financial resources and operational expertise to help transform undervalued and underperforming companies into industry leaders for long‑term success and value creation. Cerberus holds controlling or significant minority interests in companies around the world.

Cerberus Technology Solutions is an operating company and subsidiary of Cerberus Capital Management. We are a new, but growing team of AI specialists – data scientists, software engineers, and technology strategists – working to transform how an alternative investment firm with $65B in assets under management leverages technology and data. Our remit is broad, spanning investment operations, portfolio companies, and internal systems, giving the team the opportunity to shape the way the firm approaches analytics, automation, and decision‑making.

We operate with the creativity and agility of a small team, tackling diverse, high‑impact challenges across the firm. While we are embedded within a global investment platform, we maintain a collaborative, innovative culture where our AI talent can experiment, learn, and have real influence on business outcomes.