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.