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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - Data Insights - **Company:** APPFIRE TECHNOLOGIES, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Cloud Computing, Code Coverage, Code Review, Computer Programming, Continuous Integration, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Information Lifecycle Management, Python (Programming Language), Release Management, Software Deployment, Software Engineering, SQL Databases, Data Classification, Large Language Models, Snowflake, Technical Debt, Data Strategy, Data Lakes, Data Analytics, Enterprise Integration, Machine Learning Operations, Data Delivery, Terraform, Software Version Control, Data Pipelines, Docker - **Published:** June 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=51bbb9ee378eb4aa ## About the Role Do you have experience in Version control systems?, * Engineering Background: 5+ years in a data or software engineering role with a deep understanding of the full data lifecycle, modern data warehousing, and agile software development best practices. * Proven Delivery: 5+ years of experience autonomously building scalable data products, pipelines, and solutions that support company-wide systems and overarching business goals. * Project Leadership: Exceptional personal organization and multitasking skills, with the ability to work with minimal supervision while driving 3-5 concurrent cross-departmental projects. Technical Expertise * Data Warehousing & SQL: 5+ years of advanced SQL optimization and complex ETL/ELT pipeline development, with extensive, hands-on experience in Snowflake. * Advanced Python & Development: 5+ years of advanced Python programming. * Cloud Infrastructure & IaC: 5+ years of experience designing and maintaining AWS cloud environments. Strong, hands-on proficiency with Terraform and Docker is required. * Orchestration & Ingestion: Deep operational experience with Airflow for orchestration, dbt (3+ years) for transformation, and familiarity with managing Fivetran pipelines. Architecture & Practices * Pragmatic Architecture: Proven ability to design pragmatic, cost-effective architectures from scratch that prioritize security, scalability, and high performance without over-engineering. * Engineering Excellence: Incredibly strong troubleshooting skills with a ruthless dedication to reducing technical debt, optimizing CI/CD pipelines, and enforcing strict version control and testing standards. * Data Governance: Solid understanding of modern data governance principles, including automated data classification, PII masking, and row/column-level access controls. Communication & Leadership * Strategic Communication: Strong written and verbal skills, with a proven ability to translate and simplify complex technical architectures to both engineering peers and non-technical business stakeholders. * Mentorship: A team-oriented mindset with a passion for coaching and providing constructive feedback to junior team members. Bonus Points (Standout Qualifications) * MLOps Strategy: Experience in or foundational knowledge of MLOps. You can provide recommendations and establish best practices to guide our strategic expansion into this space. * Applied AI: Experience interfacing with LLMs, creating AI agents, or leveraging AI tools to accelerate daily engineering workflows (e.g., automating code reviews, CI/CD enhancements). ## Description Data is the fuel behind Appfire's global footprint. We've grown fast, and now our focus has shifted toward building the most mature, high-performing data platform in our industry. We are looking for a Senior Data Engineer to take ownership of our core infrastructure, champion engineering excellence, and help shape the future of our data ecosystem. Leveraging your expert Python, SQL, and cloud infrastructure skills, you will develop pragmatic architectures that ensure stability and performance across the organization. As a key member of our central data insights team, you will evolve our custom data lake ("firelake" built on AWS and Snowflake). To accelerate our platform optimization efforts, you will ruthlessly eliminate technical debt, resolve edge cases, and introduce modern, AI-driven development practices. This isn't just about maintaining pipelines; it's about architecting a highly secure, resilient, and scalable foundation that empowers company-wide decision-making. If you love solving complex data puzzles, driving overarching data strategy, and seeing the direct impact of your work across an entire organization, let's talk. What you'll do: Data Delivery * Solution Lifecycle Ownership: Own the complete solution development lifecycle, from driving initial requirements to building Proof of Concepts (POCs) and Minimum Viable Products (MVPs), and continuously iterating to improve and scale production solutions. * Data Delivery & Pipelines: Work closely with internal and external partners to stand up and optimize robust data delivery solutions. Build, manage, and scale complex data pipelines (ETL and reverse ETL) utilizing expert-level Python and Airflow. * Custom Integrations: Develop standard integration patterns as well as custom data pipelines that interface with atypical APIs to efficiently extend our data delivery capabilities. Data Platform & Infrastructure * Pragmatic Architecture: Architect and maintain highly efficient, cost-effective scalable data solutions and cloud infrastructure from scratch. * Platform Evolution: Be the key driver in the evolution of our custom data lake ("firelake" built on AWS/Snowflake), serving as the ultimate subject matter expert on our tech stack and data infrastructure. * Ingestion & Data Quality: Manage Fivetran and custom pipeline operations, proactively handle schema drift, and implement rigorous data quality checks to ensure we have ingested a true and accurate representation of all source systems. AI & Modern Engineering * AI-Driven Efficiencies: Spearhead AI adoption in our daily engineering workflows to automate Pull Requests, enforce new "definition of done" standards, and accelerate CI/CD, test coverage, and release management. * AI Implementation: Drive the integration of AI capabilities directly into our data solutions by interfacing with LLMs and developing intelligent assistants and agents to solve complex business problems. * Continuous Innovation: Stay on the forefront of the rapidly evolving data landscape and drive proof-of-concepts for new tools to ensure we leverage best-in-class technologies to scale quickly. Data Governance & Security * PII & Security Management: Implement advanced PII management by leveraging automated data classification techniques, applying masking policies, and enforcing sophisticated row-level and column-level security practices. * Proactive Governance: Develop and deploy robust monitoring solutions and governance strategies to ensure accurate, secure data is available on time and to the correct audience. Leadership & Collaboration * End-to-End Ownership: Autonomously lead 3-5 concurrent cross-departmental data projects, driving everything from requirements gathering and UAT to production deployment. * Strategic Communication: Partner seamlessly with business, analytics, and engineering teams, translating complex technical architectures into relatable concepts to influence stakeholders and align goals. * Engineering Excellence & Mentorship: Champion best practices, systematically reduce technical debt, write clear documentation, and provide both technical and soft-skill mentorship to junior team members. ## 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) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [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) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)