Technical Developer

Key Responsibilities:

System Design and Development:

- Design and develop DSS solutions based on business requirements, utilizing technologies such as data warehouses, data lakes, and analytics platforms.
- Implement algorithms and models for data analysis, predictive analytics, and optimization to enhance decision-making capabilities.
- Develop ETL (Extract, Transform, Load) processes to integrate data from multiple sources into the DSS platform.

Programming and Scripting:

- Write clean, maintainable code in languages such as Python, R, SQL, and Java for DSS development and integration tasks.
- Implement APIs and web services to facilitate data exchange and integration with other systems.
- Develop custom scripts and automation tools to streamline data processing and analysis workflows.

Data Modeling and Optimization:

- Design and implement data models and schemas to organize and optimize data storage for efficient querying and analysis.
- Fine-tune database queries and optimize data processing pipelines to improve system performance and scalability.
- Collaboration and Documentation:

- Collaborate with cross-functional teams including data scientists, business analysts, and software engineers to understand requirements and design effective solutions.
- Document technical specifications, data models, and system architecture to ensure clarity and maintainability of the DSS platform.
- Provide technical guidance and support to team members and stakeholders throughout the development lifecycle.

Quality Assurance and Testing:

- Develop and execute test plans to validate the functionality, performance, and reliability of DSS solutions.
- Identify and troubleshoot issues related to data quality, integrity, and consistency, and implement corrective measures as needed.

Qualifications and Skills:

- Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
- Proven experience (X years) in designing, developing, and implementing decision support systems or business intelligence solutions.
- Proficiency in programming languages such as Python, R, SQL, Java, and scripting languages.
- Strong understanding of database concepts, data modeling techniques, and SQL query optimization.
- Experience with data warehousing technologies (e.g., Snowflake, Redshift, BigQuery) and ETL tools (e.g., Apache Airflow, Talend).
- Familiarity with machine learning algorithms, statistical analysis, and data visualization techniques.
- Excellent problem-solving skills and attention to detail, with the ability to analyze complex datasets and identify actionable insights.
- Effective communication skills with the ability to collaborate with multidisciplinary teams and present technical concepts to non-technical stakeholders.
- Proactive mindset with a commitment to continuous learning and staying updated on emerging trends and technologies in data analytics and decision support systems.

Preferred Qualifications:

- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and containerization technologies (e.g., Docker, Kubernetes).
- Knowledge of distributed computing frameworks such as Apache Spark or Hadoop.
- Certification in relevant technologies or methodologies (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Data Engineer Associate).
- Experience working in agile development environments and familiarity with DevOps practices and tools.