Senior Data Engineer

Senior Data Engineer

Department / Team: Technology

Location: Remote

Employment Type: Full-time; Non-exempt

About the Firm

We are an independent sponsor firm focused on sourcing and managing private investment opportunities. Our team partners with a broad network of debt and equity investors to fund transactions across diverse industries. We pride ourselves on fostering strong, lasting relationships and delivering high-value opportunities to our investor base.

Role Summary

The Senior Data Engineer is a critical technical leadership role responsible for designing, building, and optimizing the core data infrastructure that powers the firm’s entire origination engine. This role sits at the foundation of our Go-to-Market (GTM) systems and research operations, transforming raw data from multiple sources into clean, reliable, enriched, and actionable intelligence. You will architect scalable data pipelines, ensure high data quality, enable advanced automation, and build the data platform that allows our GTM Engineers and Data Researchers to operate at maximum efficiency and scale.

Key Responsibilities

Data Pipeline Architecture: Design, build, and maintain robust, scalable ETL/ELT pipelines for ingesting, processing, and storing large volumes of lead, company, and market data from diverse sources (public records, APIs, web scraping, industry databases, etc.).

Data Platform Development: Architect and manage the firm’s data infrastructure, including data warehouses, data lakes, and real-time processing systems to support GTM automation, research, and analytics.

Data Enrichment & Quality: Lead the development of automated data enrichment processes (revenue estimation, ownership mapping, contact verification, firmographics, trigger event detection) while implementing strict data validation, deduplication, and quality assurance frameworks.

GTM Systems Integration: Build and optimize integrations between data platforms and our GTM tech stack (CRM, enrichment tools, outreach platforms, LinkedIn automation, etc.) to ensure seamless data flow and real-time synchronization.

Advanced Analytics Enablement: Create scalable data models and datasets that power dashboards, attribution models, predictive scoring, and A/B testing frameworks for origination performance.

Automation & Scalability: Develop high-performance scripts and workflows (Python, SQL, low-code platforms) to support high-volume data scraping, processing, and delivery while maintaining system reliability and cost efficiency.

Data Governance & Compliance: Establish and enforce data governance policies, security standards, and compliance practices for handling sensitive business and contact data.

Technical Leadership: Mentor GTM Engineers and Data Researchers on data best practices, troubleshoot complex data issues, and drive continuous improvement of the overall data ecosystem.

Qualifications

Required

5–8+ years of experience in Data Engineering, with a strong track record building production-grade data pipelines and platforms.

Expert-level proficiency in Python and SQL for data manipulation and pipeline development.

Hands-on experience with modern data tools and technologies (e.g., Airflow, dbt, Spark, Snowflake, BigQuery, AWS/GCP/Azure services, PostgreSQL).

Strong experience with API integrations, web scraping/automation, and data enrichment platforms.

Demonstrated ability to design scalable, reliable, and maintainable data architectures.

Preferred

Experience in Private Equity, Financial Services, or B2B lead generation environments.

Familiarity with CRM systems (HubSpot, Salesforce, Bitrix24) and GTM tools (Apollo, Clay, Zapier/Make).

Background in building data systems for sales/marketing automation or growth engineering.

Knowledge of LinkedIn data extraction techniques and public records/SEC data processing.

Skills and Competencies

Architectural Thinking: Ability to design end-to-end data solutions that balance scalability, cost, speed, and reliability.

Data Obsession: Deep commitment to data accuracy, completeness, and integrity.

Problem-Solving: Strong analytical mindset with the ability to debug complex data flows and performance issues.

Collaboration: Excellent ability to work closely with GTM Engineers, Data Researchers, and investment professionals to translate business needs into technical requirements.

Speed & Ownership: Bias for action and ability to deliver high-impact solutions quickly while maintaining long-term system health.

Reporting Structure and Work Environment

Reports To: Senior Management Team

Direct Reports: Destiny Aigbe, CEO

Work Environment:

Standard office hours 9:30 am - 5:30 pm (EST)

Remote role, with periodic strategic syncs

Compensation

Structure: Hybrid success-fee and milestone-based.

Terms: Payable only upon successful transaction close; no base salary or retainer.

Dark Alpha Capital LLC offers a competitive compensation structure for this senior technical role. Compensation includes milestone-based payments tied to the successful delivery of key data infrastructure initiatives (pipeline development, platform architecture, integrations, data quality frameworks, etc.). In addition, the Senior Data Engineer is eligible to earn a 3–5% Success Fee on cash compensation received by the Company from qualified, system-generated introductions and deals that are properly tracked and attributed. Compensation is directly linked to the performance, reliability, and business impact of the data systems built and maintained.

Compensation is 100% performance-based with no fixed base salary. The stated annual range of $120,000–$200,000 represents potential earnings based on performance and is provided as an example of achievable compensation, not a guaranteed salary.

Equal Opportunity Statement

Pay: $120,000.00 - $200,000.00 per year

Work Location: Remote