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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Ai, Inc - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $180,000.0 - $220,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Big Data, Information Engineering, Extract Transform Load (ETL), Data Systems, Software Debugging, Python (Programming Language), Operational Databases, Salesforce.Com, SQL Databases, Systems Integration, Data Ingestion, Large Language Models, Apache Spark, Pyspark, Apache Kafka, Hubspot, Data Pipelines, Databricks - **Published:** September 20, 2026 - **Apply:** https://startup.jobs/data-engineer-youcom-company-10125394 ## About the Role * 6+ years of experience in data engineering or a related field * Strong hands-on experience with Databricks, AWS (S3, Glue, Athena, EMR, etc.), and Kafka * Proficiency in Python (PySpark) and SQL for large-scale data processing * Experience building and maintaining ETL/ELT pipelines (DBT/Airflow or similar experience preferred) * Experience with data ingestion tools such as Fivetran (or similar) * Familiarity with reverse ETL / data activation workflows and syncing data to tools like Salesforce, HubSpot, Braze * Exposure to or experience with AI/ML data pipelines, including RAG architectures, vector databases, or embeddings workflows * Familiarity with agent-based systems, MCP integrations, or LLM-powered applications is a strong plus * Experience working with Finance and building finance specific metrics and pipelines is a strong plus * Understanding of data modeling and working with large-scale datasets (batch and streaming) * Experience creating dashboards and supporting reporting workflows (BI tools) for both internal and external audiences * Strong problem-solving skills and ability to debug production data issues * Strong communication skills and ability to work collaboratively across teams ## Description We are looking for a hands-on Data Engineer to help build and scale our modern data platform. In this role, you will work closely with Finance, Engineering, Product, and Analytics teams to develop reliable, high-performance data pipelines and systems., You'll contribute to both batch and real-time data processing using technologies like Databricks, AWS, kafka and several 3rd party data, while helping ensure data quality, accessibility, and usability across the organization. You'll play a key role in enabling data activation, ensuring that high-quality data flows not only into the warehouse but also outward to business tools such as Salesforce etc. Additionally, you will help power next-generation AI-driven applications, including agent-based systems and AI driven tools using OSS tech, by building robust data foundations and pipelines. This is a great opportunity for someone who enjoys solving data challenges end-to-end from ingestion to insights., * Build and maintain scalable data pipelines (batch and streaming) using tools such as Databricks, Spark, Kafka, and AWS services * Build and maintain pipelines from source systems (Salesforce, billing, product events, API logs) into clean analytics layers * Design, develop, and optimize ETL/ELT workflows using DBT, PySpark, SQL, and tools like Fivetran * Work closely with finance in developing Finance data solutions, Finance metrics and forecasting models * Partner with Finance on revenue accounting, COGS, and margin reporting * Partner closely with marketing and growth teams to enable data use cases such as segmentation, campaign targeting, and lifecycle analytics * Develop and maintain reverse ETL pipelines to sync data from the warehouse to tools like Salesforce, HubSpot, Braze, and other downstream systems * Create and manage curated datasets to support analytics, reporting, and go-to-market initiatives * Build and maintain dashboards and reporting layers to support marketing and business performance tracking * Support AI/ML and agent-based applications by preparing and serving high-quality datasets for MCP (Model Context Protocol) integrations and AI driven applications * Monitor pipeline performance, troubleshoot issues, and ensure high data reliability and quality * Implement data quality checks, validations, and alerting mechanisms across both ingestion and activation layers * Collaborate with cross-functional teams to define data contracts and ensure consistency across systems ## 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) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [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) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## 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) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)