Infinium Associate

We are seeking a skilled Magic xpa Developer with strong proficiency in .NET technologies to design, develop, and maintain enterprise applications. The ideal candidate will have hands-on experience with Magic xpa (formerly uniPaaS / eDeveloper), integration with .NET components, and solid knowledge of database systems and web services.

Key Responsibilities

• Develop, enhance, and maintain business applications using Magic xpa Application Platform.
• Integrate Magic xpa applications with .NET modules, APIs, and external systems.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications.
• Design and implement data integration, business logic, and UI functionalities within Magic xpa and .NET frameworks.
• Debug, troubleshoot, and optimize application performance.
• Participate in code reviews, unit testing, and deployment activities.
• Work with SQL Server or other RDBMS for data modeling, stored procedures, and performance tuning.
• Ensure adherence to coding standards, security practices, and documentation requirements.

Required Skills & Experience

• 5+ years of experience in Magic xpa (version 3.x or 4.x) development.
• Strong proficiency in C#, .NET Framework / .NET Core, and Visual Studio.
• Experience integrating Magic xpa applications with REST/SOAP APIs.
• Hands-on experience with SQL Server / Oracle, including complex queries and stored procedures.
• Good understanding of software development lifecycle (SDLC), agile methodologies, and version control tools (Git, TFS).
• Ability to troubleshoot runtime and build-time issues in Magic xpa and .NET environments.
• Excellent analytical, problem-solving, and communication skills.

Nice to Have

• Experience with Magic xpi (integration platform).
• Knowledge of web technologies (ASP.NET, HTML5, JavaScript).
• Exposure to cloud environments (AWS / Azure).
• Understanding of enterprise system integration and microservices architecture

About the Role:

We are seeking a talented Lead Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. As a Data Engineer, you will design, develop, and maintain robust data pipelines and infrastructure to support our organization's analytics and decision-making processes.

Responsibilities:

• Data Pipeline Development: Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into data warehouses or data lakes.
• Data Infrastructure: Design, implement, and manage data infrastructure components, including data warehouses, data lakes, and data marts.
• Data Quality: Ensure data quality by implementing data validation, cleansing, and standardization processes.
• Team Management: Able to handle team.
• Performance Optimization: Optimize data pipelines and infrastructure for performance and efficiency.
• Collaboration: Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements.
• Tool and Technology Selection: Evaluate and select appropriate data engineering tools and technologies (e.g., SQL, Python, Spark, Hadoop, cloud platforms).
• Documentation: Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and processes.

Skills:

• Strong proficiency in SQL and at least one programming language (e.g., Python, Java).
• Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks).
• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and cloud-based data services.
• Understanding of data modeling and data architecture concepts.
• Experience with ETL/ELT tools and frameworks.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a team.

Preferred Qualifications:

• Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
• Knowledge of machine learning and artificial intelligence concepts.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Certification in cloud platforms or data engineering.

About the Role:

We are seeking a talented Lead Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. As a Data Engineer, you will design, develop, and maintain robust data pipelines and infrastructure to support our organization's analytics and decision-making processes.

Responsibilities:

• Data Pipeline Development: Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into data warehouses or data lakes.
• Data Infrastructure: Design, implement, and manage data infrastructure components, including data warehouses, data lakes, and data marts.
• Data Quality: Ensure data quality by implementing data validation, cleansing, and standardization processes.
• Team Management: Able to handle team.
• Performance Optimization: Optimize data pipelines and infrastructure for performance and efficiency.
• Collaboration: Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements.
• Tool and Technology Selection: Evaluate and select appropriate data engineering tools and technologies (e.g., SQL, Python, Spark, Hadoop, cloud platforms).
• Documentation: Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and processes.

 Skills:

• Strong proficiency in SQL and at least one programming language (e.g., Python, Java).
• Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks).
• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and cloud-based data services.
• Understanding of data modeling and data architecture concepts.
• Experience with ETL/ELT tools and frameworks.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a team.

Preferred Qualifications:

• Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
• Knowledge of machine learning and artificial intelligence concepts.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Certification in cloud platforms or data engineering.