About Warmly:
Warmly is an YC, NFX, and Felicis backed Series A company changing the way B2B companies leverage high intent and chat when it comes to their inbound and outbound sales motion. There is no red tape here. We expect everyone to come in and break things in hopes to make them better and ready for scale. New ideas that are data-backed and gut-driven are what make us thrive here.
Here’s a quick video about
why you should work at Warmly.
And here are some videos about why you might not want to work at Warmly 🤣:What do you think? Would you work at Warmly?If we went back in time, which department would get to live in the Teotihuacán temples 🛕
Position Overview:
We are seeking a Data Engineer responsible for developing, constructing, testing, and maintaining data architectures. The ideal candidate will have a deep understanding of data systems, strong Python programming skills, and experience in managing large datasets and distributed systems. Additionally, the role involves working on backend features beyond data pipelines to support broader business needs.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines and ETL processes to support business requirements.• Collaborate with data scientists, analysts, and other stakeholders to understand data needs and deliver high-quality data solutions.• Ensure the integrity, availability, and performance of data systems and infrastructure.• Implement data models and database schemas that support business analytics and reporting.• Automate data workflows and improve data processing efficiency.• Monitor and troubleshoot data pipelines to ensure smooth operation.• Develop and maintain backend features that support various business functions beyond data pipelines.• Stay current with industry trends and best practices in data engineering and analytics.
Requirements:
• 3+ years of professional experience in data engineering or a related field.• Strong proficiency in Python for data processing and automation.• Experience with data processing frameworks such as Apache Spark, Hadoop, or similar.• Proficient in SQL and experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).• Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services (e.g., Redshift, BigQuery, Databricks).• Experience with version control systems, preferably Git.• Strong problem-solving skills and attention to detail.• Excellent communication and teamwork abilities.
Preferred Qualifications:
• Experience with stream-processing systems (e.g., Kafka, Flink).• Familiarity with data warehousing concepts and tools.• Understanding of data security and compliance regulations.• Experience with CI/CD pipelines and DevOps practices.• Knowledge of machine learning and data science workflows.
Tech Stack:
• Python, Elasticsearch, Azure, GCP, AWS, Flink, Pub/Sub, MongoDB, PostgreSQL, Kafka.
Compensation:USD 60000-90000
