Data & Application Engineer

• Design, develop, and maintain scalable data pipelines that extract, transform, and load (ETL/ELT) data from multiple sources into data warehouses and data lakes. 

• Design, develop, and support backend services, APIs, and application components that enable data-driven solutions. 

• Collaborate with application development teams to integrate data platforms with business applications and services. 

• Participate in self-paced learning and project delivery utilizing the Denodo platform and related technologies. 

• Design and implement data models, database schemas, and application data structures that support business and application requirements. 

• Ensure data accuracy, completeness, consistency, and reliability through data quality controls, monitoring, and governance practices. 

• Integrate and consolidate data from databases, APIs, files, third-party systems, and cloud-native services. 

• Build and optimize cloud-based data and application solutions using Azure, AWS, or Google Cloud services such as Databricks, Data Factory, Data Lake, Redshift, Aurora, and BigQuery. 

• Develop reusable frameworks, services, and automation tools to improve application and data engineering efficiency. 

• Participate in code reviews, testing, deployment activities, and CI/CD processes while following software engineering best practices. 

• Troubleshoot, debug, and optimize data pipelines, application services, and system integrations to ensure performance and reliability. 

• Collaborate effectively with project managers, product owners, architects, developers, and other stakeholders throughout the software development lifecycle. 

• Document application architectures, data flows, APIs, data models, and operational procedures to support ongoing maintenance and knowledge sharing. 

• Continuously evaluate emerging technologies and industry best practices in both application development and data engineering to drive innovation and efficiency. 

 

Required Skills & Experience 

• • Minimum 4 years of experience in Software Engineering, Data Engineering, or Application Development. 

  • Strong experience with relational databases such as SQL Server, Oracle, PostgreSQL, or MySQL. 

  • Experience designing, developing, and maintaining scalable data pipelines (ETL/ELT) for processing large volumes of data. 

  • Experience with data warehouses, data lakes, and querying structured and semi-structured data. 

  • Hands-on experience with one or more reporting and visualization tools such as Power BI, Tableau, Qlik View, Looker, or ThoughtSpot. 

  • Strong programming skills in Python, Java, Scala, or similar languages. 

  • Experience building and supporting backend applications, RESTful APIs, microservices, or distributed systems. 

  • Knowledge of software design principles, object-oriented programming, design patterns, and application architecture. 

  • Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform. 

  • Experience integrating applications and data platforms through APIs, event-driven architectures, or messaging services. 

  • Familiarity with NoSQL databases such as MongoDB, Cassandra, DynamoDB, Athena, or Redshift is an advantage. 

  • Experience with version control systems such as Git and CI/CD practices. 

  • Understanding of software development lifecycle (SDLC), Agile methodologies, testing frameworks, and deployment processes. 

  • Strong analytical, problem-solving, and communication skills.