Data Engineering Manager

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September 26

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FinStrat Management, Inc.

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Finance • SaaS • Fintech

FinStrat Management, Inc. is a financial services company that specializes in providing accounting, finance, and reporting solutions for SaaS, AI-driven, and venture-backed companies. The firm offers a range of services including fractional CFO, controller, and bookkeeping, as well as VC fund accounting and administration. Additionally, they provide portfolio company monitoring and private asset tracking and reporting services tailored for high-net-worth individuals, family offices, and VCs. FinStrat leverages AI tools to enhance financial operations and deliver GAAP-compliant financial insights through web-based dashboards.

11 - 50 employees

💸 Finance

☁️ SaaS

💳 Fintech

📋 Description

• Lead, mentor, and grow a team of data engineers responsible for building and maintaining our data infrastructure. • Define the data engineering roadmap, aligning infrastructure and analytics priorities with finance and business objectives. • Present project status, data insights, and risk assessments to executive leadership and non-technical audiences. • Analyze large and complex datasets to extract meaningful insights and drive decision-making processes. • Identify data trends, anomalies, and opportunities for improvement within datasets and communicate findings clearly to stakeholders. • Collaborate with cross-functional teams to understand business requirements and transform them into technical solutions. • Design, develop, and maintain robust data pipelines for efficient data ingestion, transformation, and storage. • Optimize and automate data workflows to improve data availability, quality, and processing efficiency. • Implement ETL processes to support analytics and reporting needs. • Build, validate, and maintain data models to support machine learning and statistical analysis needs. • Engineer and preprocess features for machine learning algorithms and ensure data quality and consistency. • Develop scalable solutions for feature storage, retrieval, and real-time model serving. • Write efficient, scalable, and well-documented Python code to support data engineering and analysis tasks. • Collaborate on code reviews, optimize code performance, and apply best practices in coding and version control. • Monitor, troubleshoot, and enhance the performance of data systems and pipelines. • Address data integrity and pipeline issues promptly to ensure reliable data availability and system uptime. • Implement monitoring and logging to preemptively detect and resolve issues. • Work closely with data scientists, analysts, and other engineers to develop cohesive data solutions. • Translate complex technical issues into non-technical language for clear communication with stakeholders. • Contribute to documentation, data standards, and best practices to foster a data-centric culture.

🎯 Requirements

• Strong proficiency in Python and familiarity with data processing libraries (e.g., Pandas, NumPy, PySpark). • Experience with SQL for data extraction and manipulation. • Experience in designing, building, and managing data pipelines, ETL workflows, and data warehousing solutions. • Ability to apply statistical methods for data analysis and familiarity with machine learning concepts. • Proven ability to troubleshoot complex data issues and continuously improve workflows for efficiency and accuracy. • Effective communication skills to convey data insights to technical and non-technical stakeholders alike. • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field. • 3+ years of experience in a data science or data engineering role.

🏖️ Benefits

• Unlimited vacation • Ongoing education and training • Bonuses and profit-sharing