Data Engineer

Looking for data problems actually worth solving? Most data engineering roles are pipeline maintenance in disguise. You inherit someone else's spaghetti, patch it quietly, and call it a day.

At Ideas2IT, you'll build data infrastructure that actually powers things: AI platforms, large-scale cloud-native applications, products that have gone on to become independently funded startups. What you'll actually do as a Data Engineer with us: - Design and build robust data pipelines and architectures on AWS or Azure - Develop and optimize ETL processes that handle large-scale structured and unstructured data from multiple sources - Work with distributed processing tools like PySpark and Pandas to move and transform data at scale - Use cloud services hands-on: Glue, Lakeformation, EMR for AWS Datafactory, Synapse, Datalake, Fabric on Azure - Model and warehouse data that feeds BI tools and supports real analytical decisions - Write clean Python or Scala to automate, integrate, and build - Collaborate with analytics and business teams to translate data needs into infrastructure that works - Contribute to tech stack decisions : your opinion on architecture matters here, not just your execution. Must-haves: - Strong SQL and hands-on experience with relational databases: MySQL, PostgreSQL, or SQL Server - Strong hands-on experience with Cloud data warehouses: AWS Redshift, Snowflake, Azure Synapse Analytics- Experience in at least one cloud environment: AWS or Azure - Proven experience building large-scale data pipelines and ETL processes - Proficiency with distributed data processing: PySpark, Pandas, Polars - Fluency in Python and/or Scala - Experience with cloud data services (Glue, Lakeformation, EMR for AWS Datafactory, Synapse, Datalake, Fabric on Azure) - Ability to handle messy, large-scale data from internal and third-party sources and make it usable Nice-to-haves: -Experience with data visualization tools: Power BI or Tableau -Familiarity with orchestration and workflow management tools -Familiarity with Data quality, testing and observability tools -Familiarity with Docker and Kubernetes Why Ideas2IT – and why now?

We operate at the intersection of a product studio and a services firm. That means your work spans industries, scales, and problem types, and not the same pipeline in a slightly different color for three years running. We've built data infrastructure for companies like Meta, Bloomberg, and Medtronic.

We've also launched six of our own products through IdeaLabs , several of which have become independently funded startups: Element5 (a $50M health-tech platform), LegacyLeap, IdeaRx, PipeCandy, and more. The shift to AI-native development is changing what great data engineering looks like. The engineers who thrive next aren't just pipeline builders; they're the ones who understand what AI systems need from data, and build infrastructure that delivers it.

You'll develop that fluency here, on real products, not in a sandbox. What that looks like day-to-day: -Autonomy to contribute to architecture and tech stack choices, not just implement them -Access to technical PoCs if there's a technology you want to explore -Internal Shark Tanks and Hackathons if you want to take an idea further -A culture that prioritises capability over tenure The hiring process – we mean business & move fast. -Send us something real: your resume, GitHub, a short note. We're not fussy. -Do a real-world challenge: a task relevant to the work, not a whiteboard puzzle. -Talk to the people you'd work with: no HR screening theatre. -Get a fast answer: yes or no, with a reason either way.

Ideas2IT is an equal opportunity employer. We hire for craft, curiosity, and drive – period. Learn more at https://www.ideas2it.com/careers