Azure Databricks Data Engineer

Job Overview:

• We are on the lookout for an enthusiastic Databricks Data Engineer who will be responsible for designing, developing, and optimizing state-of-the-art data platforms using Databricks and cloud technologies.
• The successful candidate will possess practical experience in constructing large-scale data pipelines, implementing Lakehouse architectures, and facilitating advanced analytics solutions utilizing Databricks Spark and cloud environments.
• In this position, you will collaborate closely with data architects, analysts, business stakeholders, and engineering teams to create scalable, high-performance data solutions that drive enterprise-wide digital transformation efforts.

Primary Duties:

• Design, develop, and sustain scalable data pipelines utilizing Databricks and Apache Spark.
• Construct and enhance ETL/ELT workflows for processing extensive structured and unstructured datasets.
• Create data ingestion frameworks to assimilate data from various sources, including databases, APIs, applications, and cloud storage.
• Implement and manage Lakehouse architecture utilizing Databricks and Delta Lake.
• Optimize Spark jobs and Databricks workloads for enhanced performance, scalability, and cost-effectiveness.
• Work collaboratively with analytics, BI, and business teams to comprehend data requirements and deliver reusable data assets.
• Establish data quality frameworks, monitoring solutions, and governance controls throughout data pipelines.
• Diagnose production issues and provide prompt resolutions to maintain business continuity.
• Engage in architecture reviews, code reviews, and technical discussions to advocate for best practices.
• Create and update technical documentation, reusable components, and deployment standards.

Technical Qualifications:

• 7 to 9 years of substantial 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 developing 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.
• Excellent analytical, debugging, and problem-solving abilities.

Additional Responsibilities:

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

Preferred Expertise:

Technology->Data Engineering->Databricks