We are looking for a Data Analyst to join our team in a fast-paced technical environment. The ideal candidate will be responsible for collecting, analyzing, and interpreting complex datasets to support data-driven decision-making. This role requires strong analytical skills, proficiency in data management tools, and the ability to work with cross-functional teams, including software developers, engineers, and project managers.

QUALIFICATIONS & SKILLS:

• Education: Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.
• Experience: Minimum of 2 years in data analysis, preferably in a technical or software development company.
• Technical Proficiency:
• Strong SQL skills for querying and data manipulation.
• Experience with data visualization tools (Power BI, Tableau, Looker, etc.).
• Proficiency in programming languages such as Python or R.
• Familiarity with cloud-based data platforms (AWS, Google Cloud, or Azure).
• Analytical & Problem-Solving Skills: Ability to process and interpret complex technical data.
• Communication & Collaboration: Ability to work closely with developers, engineers, and business teams to translate data insights into actionable recommendations.
• Attention to Detail: Strong focus on data integrity, accuracy, and security.

PREFERRED QUALIFICATIONS:

• Experience with big data technologies (Hadoop, Spark, Kafka).
• Knowledge of machine learning or predictive analytics.
• Understanding of software development lifecycle (SDLC) and Agile methodologies
  Job Types: Full-time, Permanen

• Extract, clean, and analyze large datasets from multiple sources, including databases, APIs, and system logs.
• Utilize SQL and programming languages (Python, R) to manipulate and process data.
• Develop dashboards and reports using Power BI, Tableau, or other visualization tools to track key performance indicators (KPIs).
• Identify trends, patterns, and anomalies to improve software performance, system efficiency, and business operations.
• Collaborate with development teams to analyze user behavior, product performance, and system reliability.
• Automate data collection and reporting processes to enhance operational efficiency.
• Ensure data accuracy, security, and compliance with company policies and industry standards.