Jobs Available at Experian

Qualifications

• Degree or Diploma in Software Development or Computer Science
• 7+ Years Software Development/Programming Experience
• Mentoring software developers
• Experience in SDLC
• Experience in Jira and Confluence or other ticketing system
• Experience in Database Design
• Experience in the Financial Sector would be advantageous

Additional Information

Principle responsibilities

• Delivery of solution, by way of code, that addresses the stated requirement and adheres to structural and performance standards.
• Support of deployed applications, as they manifest in the production environment.
• Effective communication and task management within the auspices of defined objectives and in accordance with the management reporting line.
• Adherence to SDLC policy and process, including maintenance thereof.
• Provide a strong technical direction by establishing a technical vision, resolving technical disagreements, and managing the technical quality of team deliverables.
• Ensure that the team uses appropriate engineering practices (such as CD or automated testing), invests in continual improvements to tooling or technical debt management, and that systems evolve to meet changing needs and environments.
• Assist your team with any technical challenges by using your own knowledge and experience in software development.
• Escalate and delegate tasks to appropriate team members ensuring deliverables are met and system knowledge is shared across the team.
• Participate in staff recruiting and interview processes.
• Modular responsibility for the identification and generation of recommendation where personal development is indicated or desired.
• Modular responsibility for the identification and generation of recommendation where rationalization or enhancement will provide benefit to the local unit.
• Modular responsibility to the technical development of junior, intermediate and senior programming resources.

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Qualifications

• BSc/BA in Computer Science math, software engineering, statistics, data science or a related technical field with 3 to 5 years of work experience. Microsoft SQL certification.

Functional

• Proven experience as a Data Scientist or Data Analyst.
• Experience in data warehousing, ETL processes, data mining and data modelling.
• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of Microsoft SQL Server, T-SQL, Azure and Python.
• Proficiency in data visualization tools (e.g., Power BI, Tableau).
• Analytical mind and business acumen.
• Strong math skills (e.g., statistics, algorithms).
• Problem-solving aptitude.
• Excellent communication and presentation skills.
• Ability to work independently and with team members from different backgrounds.
• Excellent attention to detail.
• A drive to learn and master new technologies and techniques.
• Working with large datasets and moving of files between different environments.
• Import and Export data from different database technologies.
• Process automation and monitoring.
• Code migration from legacy languages and systems.
• Data Cleansing
• Data profiling
• Excellent team player and collaboration skills.
• Ability to prioritize and manage multiple tasks and projects simultaneously.

Technical

Experienced and knowledgeable in the use of tools and techniques such as

• Microsoft SQL Server
• T-SQL
• Azure Data Platform Stack
• Azure Data Lakes/Blob
• Azure HDInsight (Apache Spark)
• Azure Databricks
• Python
• PL/pgSQL
• Statistics
• Additional Information

Principle responsibilities

• Identify valuable data sources and automate collection, loading and transforming processes.
• Developing and maintaining databases, data systems, and data pipelines.
• Efficient Data Engineering (ETL).
• Data investigations and anomaly detection in data.
• Manage scheduled client and business processes and deliverables.
• Undertake pre-processing of structured and unstructured data.
• Analyse large amounts of information to discover trends and patterns.
• Build predictive models and machine-learning algorithms.
• Provide rapid feedback and insight on ad-hoc requests.
• Present information using data visualization techniques.
• Propose solutions and strategies to business challenges.
• Collaborate with client and product development teams.
• Undertaking data collection, pre-processing, and analysis.
• Building models to address business problems.
• Code migration from legacy languages.
• Creating reports and presentations for business uses.
• Correlating similar data to find actionable results.
• Managing and administrating monthly business processes.
• Client and business communication.

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Qualifications

• At least 3 years of experience in data engineering or related field
• Proficiency in Source Control, T-SQL, Python, and good documentation skills
• Deep understanding of data pipeline development and management
• Experience with data warehousing, ETL processes, and big data technologies
• Excellent problem-solving skills and attention to detail
• Ability to work collaboratively with cross-functional teams.
• Bachelor's degree in Computer Science, Data Science, or related field
• Azure Architecture

This role is not suitable for full-stack or frontend developers. We are looking for a highly specialized data specialist who is passionate about creating efficient and scalable data pipelines. If you have the required skills and experience, we would love to hear from you.

Additional Information

What you will be doing:

• Develop and maintain data pipelines using our in-house developed data framework, built and maintained in Python utilizing numerous different technologies in Azure for example Synapse, Blob Storage and Redis
• Write efficient, scalable, and maintainable code
• Collaborate with cross-functional teams to ensure seamless integration of data pipelines into existing systems
• Troubleshoot and resolve issues related to data pipelines
• Create and maintain technical documentation for all data pipelines