Data Architect

Job Role:

We are seeking a highly skilled and experienced Data Architect with expertise in designing and building data platforms in cloud environments. The ideal candidate will have a strong background in either AWS Data Engineering or Azure Data Engineering, along with proficiency in distributed data processing systems like Spark.

Additionally, proficiency in SQL, data modeling, building data warehouses, and knowledge of ingestion tools and data governance are essential for this role. The Data Architect will also need experience with orchestration tools such as Airflow or Dagster and proficiency in Python, with knowledge of Pandas being beneficial. 

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Why Choose Ideas2IT

Ideas2IT has all the good attributes of a product startup and a services company. Since we launch our products, you will have ample opportunities to learn and contribute. However, single-product companies stagnate in the technologies they use. In our multiple product initiatives and customer-facing projects, you will have the opportunity to work on various technologies.

AGI is going to change the world. Big companies like Microsoft are betting heavily on this (see here and here). We are following suit.

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What’s in it for you?‍

• You will get to work on impactful products instead of back-office applications for the likes of customers like Facebook, Siemens, Roche, and more 
• You will get to work on interesting projects like the Cloud AI platform for personalized cancer treatment 
• Opportunity to continuously learn newer technologies 
• Freedom to bring your ideas to the table and make a difference, instead of being a small cog in a big wheel 
• Showcase your talent in Shark Tanks and Hackathons conducted in the company

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‍Here’s what you’ll bring‍

• Experience in designing and building data platforms in any cloud. 
• Strong expertise in either AWS Data Engineering or Azure Data Engineering 
• Develop and optimize data processing pipelines using distributed systems like Spark. • Create and maintain data models to support efficient storage and retrieval. 
• Build and optimize data warehouses for analytical and reporting purposes, utilizing technologies such as Postgres, Redshift, Snowflake, etc. 
• Knowledge of ingestion tools such as Apache Kafka, Apache Nifi, AWS Glue, or Azure Data Factory.
• Establish and enforce data governance policies and procedures to ensure data quality and security. 
• Utilize orchestration tools like Airflow or Dagster to schedule and manage data workflows. 
• Develop scripts and applications in Python to automate tasks and processes. 
• Collaborate with stakeholders to gather requirements and translate them into technical specifications. 
• Communicate technical solutions effectively to clients and stakeholders. 
• Familiarity with multiple cloud ecosystems such as AWS, Azure, and Google Cloud Platform (GCP). 
• Experience with containerization and orchestration technologies like Docker and Kubernetes.
• Knowledge of machine learning and data science concepts. 
• Experience with data visualization tools such as Tableau or Power BI. 
• Understanding of DevOps principles and practices.