What You'll Do
• Build and maintain data pipelines and ETL/ELT workflows
• Support end-to-end data integrations connecting applications, APIs, and data platforms
• Design and implement integration workflows using iPaaS tools and custom connectors
• Contribute to data modeling and cloud data platform work
• Debug pipeline and integration failures and take ownership of resolution
• Collaborate with cross-functional teams (Finance, GTM, Product, IT,HR) to deliver analytics-ready datasets
Technical Requirements
Must Have:
• Programming — Python, Java, or JavaScript (at least one)
• SQL — querying, transformations, aggregations
• APIs — REST API concepts, request/response patterns, authentication basics
• Data & Integration Concepts — pipelines, batch vs. streaming, data quality, system integrations
Good to Have:
• PySpark — distributed data processing
• Snowflake — cloud data warehouse
• Databricks — unified data & AI platform
• Apache Airflow — workflow orchestration
• Boomi — iPaaS for building integration processes and connectors
• Dimensional Modeling — star/snowflake schema, facts & dimensions
• iPaaS / Integration Patterns — middleware, event-driven architecture
What We're Really Looking For
Beyond technical skills, we care about who you are:
• Curiosity & Learning Agility — Pick up new tools and frameworks fast
• Ownership & Accountability — See tasks through, flag blockers early
• Builder's Mindset — Get your hands dirty, build from scratch
• Team Player — Collaborate openly, communicate clearly
• Growth Orientation — Take feedback well, iterate fast
Our Culture
We're a fast-moving, high-ownership team. We value transparency, directness, and results. You'll have a dedicated mentor, exposure to real production systems from Day 1, and a clear path to a full-time data engineering or integrations role based on your impact.