Allata - Data Engineer (Databricks + Informatica + Azure)
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Requirements
• Proven hands-on experience with Informatica as a data integration and ETL platform. • Strong experience with Databricks or similar distributed data processing platforms. • Core expertise in data architecture, data integrations, data warehousing, and ETL/ELT process design. • Applied experience developing and deploying custom scripts and modules for distributed computing environments (custom code execution across parallel executors and worker nodes). • Strong proficiency in SQL, Python, and PySpark (or equivalent distributed processing languages) for data transformation and processing. • Solid knowledge of cloud and hybrid relational database systems such as MS SQL Server, PostgreSQL, Oracle, Azure SQL, AWS RDS, or comparable engines. • Hands-on experience with batch and streaming data processing techniques and data compaction strategies. • Strong analytical and problem-solving skills. • Ability to work effectively in cross-functional and distributed teams. • Clear communication skills, with the ability to explain technical concepts to non-technical stakeholders. • Proactive mindset with a strong sense of ownership. • Commitment to delivering high-quality, reliable data solutions. • At Allata, we value differences.
Responsibilities
• Design, develop, and maintain scalable data pipelines using modern distributed data processing platforms and cloud environments. • Build and optimize ETL/ELT processes following industry best practices and cloud-native architectures. • Implement data models aligned with modern Data Lakehouse principles and data architecture frameworks. • Ensure data quality, consistency, and performance across ingestion, staging, and curated data layers. • Collaborate with data architects, analysts, and business stakeholders to understand complex healthcare data requirements. • Develop reusable data transformation logic and modular processing components for efficient, maintainable systems. • Support deployment processes following CI/CD and DevOps best practices. • Monitor and optimize data workflows for performance, scalability, and reliability in production environments. • Contribute to data governance, security, and compliance practices relevant to regulated healthcare environments.
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