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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Dark Capital, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $120,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Microsoft Azure, BigQuery, Databases, Data Architecture, Data Validation, Data Cleansing, Data Deduplication, Information Engineering, Data Governance, Web Scraping, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Mining, Dataspaces, Data Systems, Data Warehousing, Software Debugging, Python (Programming Language), PostgreSQL, Automation of Marketing, Salesforce.Com, SQL Databases, Data Streaming, Systems Integration, Data Processing, Real Time Systems, Snowflake, Apache Spark, Zapier, Reliability of Systems, Data Lakes, Core Data, Low-code, Data Management, Hubspot, Data Pipelines, Api Management - **Published:** June 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f68d653a407d3790 ## About the Role Do you have experience in Tooling?, * 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 ## Description 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., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Integrate your Cognitive Assistant with 3rd-party DBs and software](https://www.wearedevelopers.com/videos/249-integrate-your-cognitive-assistant-with-3rd-party-dbs-and-software) - [HR ROBO SAPIENS: Decoding AI Agents and Workflow Automation for Modern Recruitment](https://www.wearedevelopers.com/videos/1470-hr-robo-sapiens-decoding-ai-agents-and-workflow-automation-for-modern-recruitment) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)