We are looking for an experienced Databricks Data Engineer with robust hands-on expertise in Scala and the Azure ecosystem to design, build, and optimize scalable data ingestion and processing frameworks. This role involves close collaboration with clients, architects, and cross-functional teams to translate business requirements into high-quality technical solutions.
Key Responsibilities
- Understand functional and business requirements and translate them into detailed technical specifications
- Design and develop scalable frameworks and reusable components for data ingestion and processing using Azure Databricks
- Build, optimize, and maintain ETL/ELT pipelines for large and complex datasets
- Apply Spark/Scala optimization techniques to ensure performance, scalability, and reliability
- Work closely with Client Data Engineering Managers to align technical solutions with business objectives
- Collaborate with customer Architecture teams on solution design,
code reviews, and best practices
- Participate in Agile sprint-based development and deliver high-quality outputs as per project plans
- Ensure code quality, performance tuning, and adherence to data engineering standards
Required Skills & Experience
- Strong hands-on design and development experience on the Databricks platform
- Proficiency in Scala with Apache Spark
- Experience with the Azure ecosystem, including:
- Azure Data Lake Storage (ADLS Gen2)
- Azure Data Factory (ADF)
- Azure Key Vault
- Proven experience in Spark performance tuning for large datasets
- Experience designing and implementing ETL/ELT pipelines in Databricks
- Strong problem-solving skills to handle complex business logic
- Good communication skills with experience working directly with clients
📌 Sr. Data Engineer (Databricks, Scala) (India)
🏢 Informica Solutions
📍 India
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