Senior Data Engineer

The Senior Data Engineer will be responsible for developing and maintaining our software systems, applications and tools that support the efficient operation of the company services and optimise the business processes

Criteria:

• Bachelor's degree in Computer Science or related/equivalent field required; 
• or 2+ years of related experience and/or training; or the equivalent combination of education and experience.
• Experience with development of ELT/ETL processes in traditional and distributed environments including: cleaning and transforming large data sets working with various data formats (e.g. unstructured logs, XML, JSON, flat files)
• Solid SQL skills for querying relational databases (e.g. SQL Server, Oracle, MySQL, Snowflake) with a firm understanding of database optimization
• Demonstrated knowledge using and implementing reporting and visualization tools like Tableau, Pentaho, or Power BI
• Experience with data modeling (conceptual, logical and physical), dimension modeling (snowflake, star)
• Familiarity with Linux tools and shell scripting
• Experience with Bash/Shell scripting
• Experience with statistical analysis or visualization in R, Python and Java
• Knowledge of telecommunications industry
• Excellent  problem solving and analytical skills

 MAJOR DUTIES 

• Develop and maintain data pipelines to collect data from various sources, including databases, APIs, and streaming platforms.
• Implement data ingestion processes to ensure the availability, reliability, and scalability of data.
• Design and build ETL (Extract, Transform, Load) processes to transform raw data into structured and usable formats.
• Perform data cleansing, enrichment, and normalization to ensure data quality and consistency.
• Create and manage data warehouses, data lakes, or storage solutions to store and organize data for analysis.
• Optimize data storage and retrieval mechanisms for performance and cost-efficiency.
• Collaborate with data analysts and data scientists to design data models and schema for analytical purposes.
• Develop and maintain data dictionaries and documentation for data assets.
• Implement data quality controls and ensure data integrity throughout the data lifecycle.
• Define and enforce data governance policies, including access controls and data retention policies.
• Monitor and fine-tune data pipelines and processes for optimal performance.
• Identify and resolve data-related performance bottlenecks and issues.
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand -data requirements and deliver data solutions. enhancements, and knowledge transfer within the team.
• Provide technical support and troubleshoot data-related issues for internal users, ensuring timely resolution and effective communication.

Only shortlisted candidates will be contacted.