Senior Data Engineer

Were looking for a skilled Data Engineer to own and scale our data processing pipelines and search infrastructure. This role is ideal for someone with strong AWS and Elasticsearch expertise, a passion for clean data, and an interest in applying LLMs or semantic search enhancements to real-world problems.

Responsibilities

• Own and maintain our data pipelines using AWS Glue (PySpark) and S3

• Process and manage large-scale datasets stored in Elasticsearch and MongoDB

• Build and optimize workflows for data transformation, cleaning, and normalization

• Improve the performance and relevance of our search system through algorithmic tuning and semantic enhancements (e.g., LLMs, DeepL, embeddings)

• Monitor data quality, handle schema evolution, and ensure operational stability

• Collaborate with backend and product teams to ensure fast, reliable, and accurate data-driven features

Must-Have Skills

• Solid experience with AWS data engineering tools (Glue, S3, Lambda)

• Strong knowledge of Elasticsearch (query design, aggregations, performance tuning)

• Proficiency in Python, especially with PySpark and Pandas

• Experience with data quality, schema evolution, and pipeline monitoring

• Familiarity with LLMs, embeddings, or search ranking improvements is a plus

• Backend development skills in Node.js or general JavaScript knowledge is advantageous

• Previous experience with B2B datasets, contact enrichment, or lead intelligence is highly valuable

Why Join

• Shape the tech direction and build from the ground up

• Collaborate closely with the founder on product execution

• Work with real user feedback and fast iteration cycles

Signs This Role Isn't for You

• You're looking for a cushy 9-5 job with well-defined tasks and processes

• You dislike fast-moving environments where things might break

• You're not excited about testing new ideas, shipping quickly, and gathering feedback on the fly