Data and Automation Engineer - Python
- Role
- Data Engineering
- Experience
- Senior
- Employment
- Full-time
- Company size
- Startup
The listing doesn't say where it hires from. Check the description or the employer's site before applying.
No BS summary
Data/automation engineer with 3–7+ years in data engineering, marketing ops, sales ops, or a related technical field. Must be US-based, strong in Python, Databricks, PySpark, SQL, Delta Lake, SaaS API integrations, and AI coding tools.
Core skills
Required skills
Optional skills
About the Role We're looking for an AI-Enabled Data & Automation Engineer who thrives on solving complex data challenges through software and automation. You'll be responsible for building scalable data pipelines, integrating data from multiple SaaS platforms, developing automation that powers lead generation and enrichment, and leveraging AI to dramatically accelerate development. You'll work with modern technologies including Python, Databricks, and LLM-powered tools to build solutions that directly impact business growth. This role is ideal for someone who enjoys building, experimenting with new technologies, and continuously finding better and faster ways to solve problems. Responsibilities Design, build, and maintain scalable data pipelines for ingesting, processing, and enriching large datasets. Develop Python-based automation for data collection, transformation, validation, and workflow orchestration. Build and optimize data processing workflows using Databricks, PySpark, SQL, and Delta Lake. Integrate and process data from multiple SaaS platforms through REST APIs and other integrations. Develop scalable workflows for lead generation, company and contact enrichment, and sales intelligence. Implement processes for data cleansing, deduplication, entity resolution, normalization, and contact/company matching. Process structured, semi-structured, and JSON data from a variety of internal and external sources. Collaborate with product, engineering, and go-to-market teams to translate business requirements into scalable technical solutions. Identify opportunities to automate repetitive processes and improve operational efficiency. Continuously evaluate and adopt new AI tools and technologies that improve development speed and data quality. Requirements Technical Skills 3–7+ years of experience in Data Engineering, Marketing Operations, Sales Operations, or a related technical field. Strong Python programming skills with experience in data processing, automation, and API integrations. Experience with Databricks, PySpark, SQL, and Delta Lake. Experience integrating and processing data from multiple SaaS platforms via APIs. Strong understanding of lead enrichment, data quality, deduplication, entity resolution, and contact/company matching. Experience working with structured, semi-structured, and JSON data. Familiarity with Git and modern software development practices. Undergraduate Degree in Computer Science, Engineering, Physics or other relevant degree AI & Productivity Heavy user of AI coding tools such as Cursor, Claude Code, GitHub Copilot, ChatGPT, or similar AI development assistants. Demonstrated ability to leverage AI to accelerate software development, automate workflows, improve data quality, and increase productivity. Comfortable rapidly prototyping, testing, and iterating using AI-assisted development. Preferred Qualifications Hands-on experience with lead generation and sales intelligence platforms such as Apollo, Clay, LinkedIn Sales Navigator, ZoomInfo, or similar tools. Experience with CRM platforms such as Salesforce or HubSpot. Familiarity with LLM APIs and AI-powered applications. Experience working in fast-paced startup environments. Strong communication skills with the ability to work cross-functionally and take ownership from concept through delivery. Plum AI, Inc looks forward to applicants from US based candidates. We are not working with outside recruiters. We appreciate individual, not AI generated, applications. We may disqualify applicants who use AI in any part of the interview process. Benefits What We Offer: A fast-paced, collaborative startup culture with high visibility. Autonomy, flexibility, and a flat corporate structure that gives you the opportunity for your direct input to be realized and put into action. Opportunity to make a meaningful impact in building a company and culture. Equity in a financial technology startup. Generous health, dental, and vision coverage for employees and family members + 401K. Eleven paid holidays and unlimited discretionary vacation days. Competitive compensation and bonus potential.
What you'll do
- Design, build, and maintain scalable data pipelines for ingesting, processing, and enriching large datasets.
- Develop Python-based automation for data collection, transformation, validation, and workflow orchestration.
- Build and optimize data processing workflows using Databricks, PySpark, SQL, and Delta Lake.
- Integrate and process data from multiple SaaS platforms through REST APIs and other integrations.
- Develop scalable workflows for lead generation, company and contact enrichment, and sales intelligence.
- Implement processes for data cleansing, deduplication, entity resolution, normalization, and contact/company matching.
- Process structured, semi-structured, and JSON data from a variety of internal and external sources.
- Collaborate with product, engineering, and go-to-market teams to translate business requirements into scalable technical solutions.
- Identify opportunities to automate repetitive processes and improve operational efficiency.
- Continuously evaluate and adopt new AI tools and technologies that improve development speed and data quality.
What they require
- 3–7+ years of experience in Data Engineering, Marketing Operations, Sales Operations, or a related technical field.
- Strong Python programming skills with experience in data processing, automation, and API integrations.
- Experience with Databricks, PySpark, SQL, and Delta Lake.
- Experience integrating and processing data from multiple SaaS platforms via APIs.
- Strong understanding of lead enrichment, data quality, deduplication, entity resolution, and contact/company matching.
- Experience working with structured, semi-structured, and JSON data.
- Familiarity with Git and modern software development practices.
- Undergraduate Degree in Computer Science, Engineering, Physics or other relevant degree
- Heavy user of AI coding tools such as Cursor, Claude Code, GitHub Copilot, ChatGPT, or similar AI development assistants.
- Demonstrated ability to leverage AI to accelerate software development, automate workflows, improve data quality, and increase productivity.
- Comfortable rapidly prototyping, testing, and iterating using AI-assisted development.
- Preferred: Experience working in fast-paced startup environments.
- Preferred: Strong communication skills with the ability to work cross-functionally and take ownership from concept through delivery.
- US based candidates.
- Individual, not AI generated, applications.
- May disqualify applicants who use AI in any part of the interview process.
Benefits
- A fast-paced, collaborative startup culture with high visibility.
- Autonomy, flexibility, and a flat corporate structure that gives you the opportunity for your direct input to be realized and put into action.
- Opportunity to make a meaningful impact in building a company and culture.
- Equity in a financial technology startup.
- Generous health, dental, and vision coverage for employees and family members + 401K.
- Eleven paid holidays and unlimited discretionary vacation days.
- Competitive compensation and bonus potential.