Requirements

Expected technologies

Python

SQL

Java

Apache Spark

Hadoop

AWS

Azure

Google Cloud

Tableau

Power BI

Our requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• 5+ years of experience in data engineering or related roles, with a strong understanding of data integration and modeling.
• Proficiency in programming languages such as Python, SQL, or Java, and experience with data processing frameworks (e.g., Apache Spark, Hadoop).
• Familiarity with data warehousing solutions and ETL (Extract, Transform, Load) processes.
• Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud) and data storage solutions (e.g., relational databases, NoSQL databases).
• Strong analytical skills and the ability to present complex data insights clearly to stakeholders.
• Excellent problem-solving abilities and a proactive approach to identifying and resolving issues.
• Preferred:
• Experience with data visualization tools (e.g., Tableau, Power BI) and business intelligence practices.
• Knowledge of data governance frameworks and best practices.
• Familiarity with Agile methodologies and project management tools.

Your responsibilities

• Data Analysis and Synthesis
• Undertake data profiling and source system analysis
• Present clear insights to colleagues to support the end use of the data
• Data Development Process
• Design, build and test data products that are complex or large scale
• Build teams to complete data integration services
• Data Innovation
• Understand the impact on the organization of emerging trends in data tools, analysis techniques and data usage
• Data Integration Design
• Select and implement the appropriate technologies to deliver resilient, scalable and future-proofed data solutions and integration pipelines
• Data Modeling
• Produce relevant data models across multiple subject areas
• Explain which models to use for which purpose
• Understand industry-recognized data modelling patterns and standards, and when to apply them
• Compare and align different data models
• Metadata Management
• Design an appropriate metadata repository and present changes to existing metadata repositories
• Understand a range of tools for storing and working with metadata
• Provide oversight and advice to more inexperienced members of the team
• Problem Resolution
• Respond to problems in databases, data processes, data products and services as they occur
• Initiate actions, monitor services and identify trends to resolve problems
• Determine the appropriate remedy and assist with its implementation, and with preventative measures
• Programming and Build
• Use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts from agreed specifications and subsequent iterations
• Collaborate with others to review specifications where appropriate
• Technical Understanding
• Understand the core technical concepts related to the role, and apply them with guidance
• Testing
• Review requirements and specifications, and define test conditions
• Identify issues and risks associated with work
• Analyze and report test activities and results