Data Engineer – (Data & AI)

What You'll Do

• Design, develop, and maintain scalable data pipelines and data integration solutions across on-premise, cloud, and hybrid environments.
• Build and optimize data models, ETL/ELT processes, and data services to support analytics, reporting, and operational use cases.
• Support Master Data Management (MDM) initiatives by implementing data integration, data quality, and data governance controls.
• Work closely with Data Scientists, Analysts, and business stakeholders to understand requirements and deliver reliable data solutions.
• Develop and maintain APIs, microservices, and data services that enable efficient consumption of enterprise data.
• Implement automation to improve operational efficiency, reduce manual effort, and enhance data platform reliability.
• Monitor, troubleshoot, and optimize data pipelines and platform performance to meet service-level expectations.
• Contribute to platform operations, incident resolution, and continuous improvement initiatives.
• Participate in code reviews, testing, documentation, and adoption of engineering best practices.
• Collaborate effectively with cross-functional teams to deliver projects and business outcomes.

What You'll Need

• Experience building and maintaining data lakes, data warehouses, and large-scale data processing pipelines.
• Proficiency in SQL and experience working with both relational and NoSQL databases.
• Hands-on experience with big data technologies such as Spark, Kafka, Hive, and HBase.
• Experience with programming such as Python, Java, or Scala.
• Familiarity with data governance, data quality, metadata management, and data lineage concepts.
• Experience working in Agile development environments and applying software engineering best practices.
• analytical, problem-solving, and communication skills.
• Experience with Cloudera Data Platform (CDP) or similar enterprise data platforms.
• Experience with ETL and orchestration tools such as Talend, Azure Data Factory, or similar technologies.
• Exposure to cloud data services on Azure, AWS, or GCP.
• Familiarity with Master Data Management (MDM) concepts and tools.
• Experience with modern data lake technologies such as Delta Lake or Databricks.
• Exposure to metadata management and data governance platforms.
• Ability to work effectively with multiple stakeholders in a fast-paced environment.