Azure Databricks Data Engineer

Job Overview:

• We are looking for an enthusiastic Databricks Data Engineer to architect, develop, and enhance cutting-edge data platforms utilizing Databricks and cloud technologies.
• The perfect candidate will possess hands-on experience in constructing large-scale data pipelines, implementing Lakehouse architectures, and enabling sophisticated analytics solutions using Databricks Spark and cloud environments.
• In this position, you will collaborate with data architects, analysts, business stakeholders, and engineering teams to provide scalable, high-performance data solutions that underpin enterprise-wide digital transformation efforts.

Core Responsibilities:

• Design, develop, and sustain scalable data pipelines with Databricks and Apache Spark.
• Construct and refine ETL/ELT workflows for processing extensive structured and unstructured datasets.
• Create data ingestion frameworks to amalgamate data from diverse sources, including databases, APIs, applications, and cloud storage.
• Implement and oversee Lakehouse architecture using Databricks and Delta Lake.
• Enhance Spark jobs and Databricks workloads for optimal performance, scalability, and cost-effectiveness.
• Engage with analytics, BI, and business teams to ascertain data requirements and deliver reusable data assets.
• Establish data quality frameworks, monitoring solutions, and governance controls across data pipelines.
• Resolve production issues promptly to ensure uninterrupted business operations.
• Participate in architecture reviews, code reviews, and technical discussions to advocate for best practices.
• Develop and maintain technical documentation, reusable components, and deployment standards.

Technical Qualifications:

• 3-5 years of experience in Data Engineering and Big Data technologies.
• Extensive hands-on experience with Databricks.
• Expertise in PySpark or Spark SQL for distributed data processing.
• Strong SQL proficiency with a background in query optimization and performance tuning.
• Experience in designing and implementing ETL/ELT pipelines.
• Hands-on experience with Delta Lake, DataFrames, and Spark architecture.
• Understanding of data warehousing concepts, dimensional modeling, and data lake architectures.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with Git-based source code management and DevOps methodologies.
• Strong analytical, debugging, and problem-solving capabilities.

Additional Responsibilities:

• Infosys Data Analytics practice supports organizations in modernizing their data landscape through cloud-native architectures, advanced analytics, AI, and intelligent data platforms.
• As a Databricks Data Engineer, you will be involved in enterprise-scale data modernization initiatives, including Lakehouse implementations, cloud migrations, real-time analytics, and AI-ready data ecosystems.

Preferred Skills:

Technology->Data Engineering->Databricks