As a Business Intelligence Engineer at Adpedia, you will be responsible for designing, developing,
and maintaining our business intelligence solutions and data infrastructure.
You will collaborate with cross-functional teams to gather requirements, implement data models, create visualizations,
and deliver actionable insights that drive strategic business decisions. Your expertise in data engineering, analytics,
and visualization tools will be essential in optimizing our data processes and enhancing our overall data strategy.
Qualification
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; Master's degree is a plus.
3 years of professional experience in business intelligence, data engineering, or a related role.
Proficiency in SQL for querying and manipulating large datasets.
Strong programming skills in languages like Python, Java, or similar.
Experience with ETL processes, data warehousing, and data integration.
Solid understanding of database design principles and data modeling.
Ability to work collaboratively in cross-functional teams and communicate complex technical concepts to non-technical stakeholders.
Strong problem-solving skills and attention to detail.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark) is a plus.
Excellent communication, interpersonal, and organizational skills.
Responsibilities
Collaborate with stakeholders to understand business requirements and translate them into data and reporting solutions
Design, develop, and maintain robust and scalable data models, ETL pipelines, and data warehouses to ensure data accuracy and availability.
Implement efficient data integration processes, transforming raw data into actionable insights using ETL tools and programming languages (e.g., SQL, Python, etc.).
Build interactive and visually appealing dashboards, reports, and data visualizations using in-house built platform based on react sourced by GCP for business users.
Monitor data quality, troubleshoot data anomalies, and ensure data integrity and consistency across various sources.
Collaborate with data scientists and analysts to understand analytical requirements and provide the necessary data support for advanced analytics and machine learning projects.
Participate in code reviews, provide mentorship to junior team members, and contribute to continuous improvement initiatives.
