About Enlyft
Data and AI are at the core of the Enlyft platform. Our big data engine indexes billions of structured and unstructured documents and leverages advanced machine learning to infer the technology footprint of millions of businesses worldwide.
The complex and evolving relationships between companies and technologies form a large-scale technological graph that powers Enlyft’s predictive intelligence platform. By combining our proprietary technology graph with firmographic signals and customers’ CRM data, our models help organizations identify high-propensity accounts and drive more effective go-to-market strategies.
Our data platform is the backbone of Enlyft’s AI-native platform, enabling large-scale data processing that powers machine learning models, insights engines, and customer-facing applications. It also provides the foundation for building agentic workflows and intelligent automation, helping GTM teams make smarter, data-driven decisions at scale.
What you will do
- Lead the architecture and design of scalable data platforms and large-scale distributed data processing systems
- Build and evolve robust data pipelines for ingestion, processing, enrichment, and transformation of structured and unstructured datasets
- Design and implement high-performance data models that support machine learning pipelines, analytics, and customer-facing applications
- Establish and drive best practices for data quality, observability, governance, and reliability across the data platform
- Partner closely with data science teams to support feature engineering, model training pipelines, and production ML systems
- Evaluate and introduce modern data platform technologies to improve scalability, performance, and developer productivity
- Drive adoption of LLMs and AI-powered tooling to improve data engineering productivity and apply AI-driven approaches for data discovery, pipeline automation, metadata enrichment, and data quality
- Mentor engineers and provide technical leadership across the data platform team
What we’re looking for
- Bachelor's degree or higher in Computer Science, Engineering or related field with 13+ years of experience in data engineering with a strong focus on designing and building scalable data platforms and products
- Deep expertise in data modeling, distributed data processing, and large-scale ETL/ELT systems to build data lakes, data warehouses and modern lakehouse architectures
- Strong experience with distributed data technologies (Spark, Kafka, Hadoop, or similar frameworks) and programming expertise in Python and SQL
- Experience with cloud such as AWS, Azure or GCP and related services (S3, Redshift, BigQuery, Dataflow)
- Proven expertise in data quality checks to ensure data accuracy, completeness, consistency, and timeliness
- Hands-on experience using LLMs, AI-assisted development tools, or AI-driven workflows to improve engineering productivity and automate development processes
- Excellent problem-solving in fast-paced, collaborative environment, coupled with strong communication for effective interaction with tech & non-tech stakeholders
Why join Enlyft
- A top-notch culture that is customer-obsessed, transparent, and constantly strives for excellence
- A top-notch team where you will learn, grow, and collaborate with talented engineers and data scientists
- The opportunity to work on cutting-edge AI systems and agentic workflows, helping shape both how we build software and how our customers leverage AI in their go-to-market strategies
- Competitive pay and great benefits
Enlyft is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
