‍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.

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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.

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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 workplace: 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

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Nice-to-haves

Experience with data visualization tools: Power BI or Tableau
Familiarity with orchestration and workflow management

📌 Data Engineer (Chennai)
🏢 Idea Nuggets
📍 Chennai