Azure Databricks Data Engineer

Job Overview:

• We are looking for a driven Databricks Data Engineer to create, develop, and enhance modern data platforms utilizing Databricks and cloud technology solutions.
• The ideal candidate will possess hands-on experience in constructing large-scale data pipelines, implementing Lakehouse architectures, and facilitating advanced analytics solutions using Databricks Spark within cloud environments.
• In this position, you will collaborate with data architects, analysts, business stakeholders, and engineering teams to deliver scalable, high-performance data solutions that support enterprise-wide digital transformation efforts.

Main Responsibilities:

• Design, develop, and sustain scalable data pipelines utilizing Databricks and Apache Spark.
• Construct and enhance ETL/ELT workflows for managing large-scale structured and unstructured datasets.
• Create data ingestion frameworks to consolidate data from various sources, including databases, APIs, applications, and cloud storage.
• Implement and oversee Lakehouse architecture through the use of Databricks and Delta Lake.
• Optimize Spark jobs and Databricks workloads to achieve performance, scalability, and cost efficiency.
• Work collaboratively with analytics, BI, and business teams to define data requirements and provide reusable data assets.
• Establish data quality frameworks, monitoring solutions, and governance controls across data pipelines.
• Diagnose and resolve production issues promptly to ensure seamless business operations.
• Engage in architecture reviews, code reviews, and technical discussions to advocate for best practices.
• Produce and maintain technical documentation, reusable components, and deployment standards.

Technical Qualifications:

• 2-3 years of experience in Data Engineering and Big Data technologies.
• Extensive hands-on experience with Databricks.
• Proficiency in PySpark or Spark SQL for distributed data processing.
• Solid SQL skills 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.
• Familiarity with cloud platforms such as Azure, AWS, or GCP.
• Knowledge of Git-based source code management and DevOps methodologies.
• Strong analytical, debugging, and problem-solving abilities.

Additional Duties:

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

Preferred Competencies:

Technology->Data Engineering->Databricks