Data Analyst / Cloud Engineer at Intelics Solutions

Job Summary

• We are seeking a skilled and analytical Data Analyst / Cloud Engineer to collect, process, analyze, and interpret data while designing, deploying, and maintaining secure, scalable cloud infrastructure.
• The successful candidate will combine data analytics expertise with cloud computing knowledge to support data-driven decision-making, optimize business processes, and ensure reliable cloud-based systems.

Key Responsibilities
Data Analysis and Reporting:

• Collect, clean, transform, and analyze structured and unstructured data from multiple sources.
• Develop dashboards, reports, and visualizations using Power BI, Tableau, or similar tools.
• Use SQL, Excel, Python, or R to extract insights and identify trends, patterns, and business opportunities.
• Develop and maintain key performance indicators (KPIs) and performance reports.
• Validate data accuracy, maintain data quality, and document analytical processes.
• Collaborate with business stakeholders to understand reporting requirements and deliver actionable insights.
• Support forecasting, statistical analysis, and data-driven decision-making.

Cloud Engineering and Infrastructure:

• Design, deploy, configure, and maintain cloud infrastructure on platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Manage cloud storage, virtual machines, databases, networking, and computing resources.
• Implement cloud security controls, identity and access management (IAM), encryption, and backup solutions.
• Monitor cloud infrastructure performance, availability, and resource utilization.
• Automate infrastructure deployment and routine operational tasks using scripting and Infrastructure as Code (IaC) tools.
• Troubleshoot cloud infrastructure issues and optimize system performance and costs.
• Support cloud migration, disaster recovery, and business continuity initiatives.
• Implement monitoring, logging, and alerting to maintain system reliability.

Data Engineering and Cloud Integration:

• Build and maintain data pipelines for extracting, transforming, and loading data (ETL/ELT).
• Integrate cloud-based data sources, storage services, and analytical platforms.
• Support the development of cloud data warehouses and data lakes.
• Automate data processing workflows and improve data accessibility.
• Ensure data governance, privacy, security, and compliance with relevant organizational policies.

Key Performance Indicators (KPIs)

• Accuracy, consistency, and timeliness of data reports.
• Reliability and availability of cloud infrastructure.
• Efficiency and performance of data pipelines.
• Reduction in cloud operating costs and resource wastage.
• Compliance with security and data governance requirements.
• Timely resolution of technical issues.
• Quality and business impact of analytical insights.

Required Qualifications

• Bachelor’s Degree in Computer Science, Data Science, Statistics, Information Technology, Engineering, or a related field, or equivalent practical experience.
• Demonstrable experience in data analysis, cloud engineering, or a related technical role.
• Strong knowledge of SQL, Excel, and data visualization tools.
• Experience with at least one major cloud platform: AWS, Microsoft Azure, or GCP.
• Knowledge of Python or another programming or scripting language.
• Understanding of databases, data pipelines, networking, and cloud security fundamentals.
• Strong analytical, problem-solving, communication, and documentation skills.

Technical Skills:

• Data Analytics: SQL, Excel, Python, Power BI, Tableau.
• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform.
• Databases: PostgreSQL, MySQL, SQL Server, or cloud-native databases.
• Data Engineering: ETL/ELT, data pipelines, data warehouses, data lakes.
• Cloud Operations: IAM, networking, monitoring, backups, and cost optimization.
• Automation: Python, Bash, PowerShell, Terraform, or similar tools.
• Version Control: Git and GitHub or equivalent platforms.

Preferred Qualifications:

• Relevant cloud certifications, such as AWS Certified Solutions Architect, Microsoft Azure certifications, or Google Cloud certifications.
• Microsoft Power BI Data Analyst certification or equivalent analytics credentials.
• Experience with cloud data services, such as Amazon Redshift, Azure Synapse Analytics, BigQuery, or Snowflake.
• Familiarity with Docker, CI/CD pipelines, and DevOps practices.
• Knowledge of data governance, information security, and regulatory compliance.
• Experience working with cross-functional teams in an Agile environment.

Core Competencies:

• Analytical thinking and attention to detail.
• Cloud infrastructure management.
• Technical troubleshooting and problem-solving.
• Effective communication and stakeholder engagement.
• Project management and teamwork.
• Continuous learning and adaptability.