Business Intelligence (Bi) & Data Engineer

Details of the offer

Job title : Business Intelligence (BI) & Data Engineer
Job Location : Gauteng, Johannesburg

Deadline : December 21, 2024

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We are seeking a skilled Business Intelligence (BI) & Data Engineer to join our team. The ideal candidate will have a strong background in data engineering combined with a deep understanding of business intelligence tools and methodologies. You will design, develop, and optimize data pipelines, ensure data integrity, and deliver business intelligence solutions that drive informed decision-making across the organization.


Responsibilities:

Data Engineering Responsibilities:


Design, build, and maintain scalable, reliable, and efficient data pipelines for both structured and unstructured data sources.
Develop, test, and deploy ETL (Extract, Transform, Load) processes to ensure data availability for reporting and analytics.
Collaborate with Data Scientists and Analysts to provide clean, reliable data for analysis.
Optimize and monitor database performance, ensuring that data infrastructure meets business needs.
Manage data storage systems and ensure the integrity and accuracy of data across platforms.
Work with cloud platforms (AWS, GCP, or Azure) to deploy data solutions and manage data infrastructure.
Business Intelligence Responsibilities:
Design, develop, and maintain BI dashboards and reports to deliver actionable insights on business performance metrics.
Work closely with stakeholders to gather business requirements and translate them into technical solutions using BI tools.
Analyze complex datasets to uncover trends and provide insights to drive business decisions.
Ensure data accuracy and consistency across reports and dashboards, optimizing existing solutions for performance and user experience.
Enhance and maintain the data warehouse, ensuring it supports reporting and analytics needs.
Stay updated on emerging BI and data engineering tools, suggesting improvements and upgrades when necessary.


General Responsibilities:


Ensure compliance with data security, privacy, and governance policies.
Collaborate with cross-functional teams (e.g., Finance, Marketing, Operations) to support data-driven decision-making across the business.
Document data workflows, ETL processes, and BI solutions for future reference and scalability.


Qualifications:


Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
3-5+ years of experience in a combined Data Engineering and Business Intelligence role or similar.
Strong proficiency in SQL and hands-on experience with ETL tools such as Airflow, SSIS, or Talend.
Proficiency with BI tools like Tableau, Power BI, Looker, or QlikView.
Experience with programming languages such as Python, Java, or Scala.
Expertise in data warehousing concepts and technologies such as Snowflake, Redshift, or BigQuery.
Experience working with cloud platforms (e.g., AWS, GCP, Azure).
Knowledge of both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra).
Understanding of data governance, data security, and compliance standards.
Experience with real-time data processing and data streaming tools such as Kafka is a plus.


Skills:


Strong problem-solving skills with an ability to analyze and interpret complex data.
Excellent attention to detail, ensuring accuracy and reliability in both data engineering and BI solutions.
Ability to work cross-functionally, bridging technical and business teams.
Strong communication skills to translate technical concepts into business-friendly insights.
Self-driven with the ability to manage multiple projects and meet deadlines.
Experience with Agile methodologies and project management tools (e.g., JIRA, Trello).


Preferred Qualifications (Optional):


Certifications in cloud platforms (AWS, Azure, GCP) or BI tools (e.g., Tableau Certified Associate, Microsoft Power BI Certification).
Experience with advanced analytics, machine learning pipelines, or predictive modeling.
Familiarity with containerization and orchestration tools like Docker and Kubernetes.



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