Data Engineer

The Data Engineer plays a key role in designing, building and optimising data solutions. This role leads and guides a team of data engineers across data architecture, ETL pipelines and business rule transformation. Expertise in data integration, processing and visualization ensures the delivery of high-quality data solutions.

Key Responsibilities:

Lead and guide a team of data engineers as part of a project.

Design data architecture (e.g. data warehouse, data lake) and ETL pipelines.

Analyse business rules with users and translate them into mapping and functional specification documents.

Implement, and lead a team in, the following:

o Developing data ingestion, integration and extraction pipelines with the data lake.

o Writing clear and concise documentation, including the business logic implemented for each required transformation.

o Troubleshooting and resolving issues with users on the implemented solution.

o Enforcing and adhering to defined processes, procedures, best practices and standards.

o Creating visualizations using modern platforms (e.g. Tableau, Microsoft Power BI), where required.

Requirements:

Minimum 3 to 5 years of experience in data engineering or a related field.

Bachelor's degree in Computer Science, Information Technology, Data Science or a related discipline.

Hands-on ETL experience across design, mapping and development, adhering to standard practices.

Talend certification is required(e.g. Qlik Talend Core Certified Data Integration Developer, or Talend Data Integration Certified Developer using Talend Studio) and exposure to Talend ETL tool compulsory to have.

Experienced and able to perform ETL and data pipelines design and development using Talend solution.

Skills & Competencies:

Strong grounding in database structures, theories, principles and practices, including data warehouse design.

Preferred: experience with a major cloud or data platform (AWS, Azure, Google Cloud, Alibaba Cloud, Snowflake, Databricks).

Preferred: knowledge of big data querying tools such as Hive and Hue.

Preferred: experience with the Talend ETL tool.

Good to have: Python, data APIs, unstructureddata and the Hadoop ecosystem.

Have a diverse and thorough awareness/understanding of key enterprise data management best practices and guidelines.

Have entry level understanding of state of the art market ETL and data management solutions such as but not limited to : Informatica, AWS Glue, Alation, Talend Data Catalog, Precisely, IBM Data Stage, Qlik Replicate etc.