Data and Automation Engineer
New
P
Plum IncFinancial Technology
United States. Austin, Texas, United States. Las Vegas, Nevada, United States. Atlanta, Georgia, United StatesFull-TimeMiddle
SalaryCompetitive compensation and bonus potential.
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Job Details
- Experience
- 3–7+ years of experience in Data Engineering, Marketing Operations, Sales Operations, or a related technical field.
- Required Skills
- PythonSQLGitData engineeringJSONDatabricksPySpark
Requirements
- 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.
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.
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