Mid-Level Data Engineer

We are looking for an experienced Mid Level Data Engineer to join us in driving significance together.

Primary Duties and Responsibilities:

The Data Engineer will have a knack for data analysis, data manipulation and data modelling. The consultant will be responsible for understanding and driving the overall technical vision and planning of a client's organisation and translating business needs into technical strategy.

Required Qualifications:

· Tertiary degree, diploma or certificate in a related field (BSc Computer Science, B.IT or Informatics related degrees).
· DP-203: Data Engineering on Microsoft Azure Certification.

Experience and Knowledge:

· 5- 8 years’ working experience as a Data Engineer / Database Developer.
· Experience in data mining, large scale data modelling and business requirements gathering/analysis.
· Understanding and working experience in data integration and transformation.
· Experience implementing data modelling methodologies like Dimensional Modeling and / or Data Vault.
· Working knowledge of data quality processes and master data management.
· Experience implementing design support systems using Database Management Systems (DBMS) such as SQL Server or Oracle.
· Designing and implementing data integration and ETL solutions using SSIS, Azure Data Factory and / or SQL Server.
· Understanding of several Big Data technologies like Hadoop, MapReduce and Spark.
· Experience in database query languages such as T-SQL, ANSI SQL, PL/SQL.
· Some experience developing software solutions using Visual Basic, C++, C#, Java or Python.
· Experience using SQL Server management Studio and Visual Studio.
· Azure SQL databases, Azure Synapse (Previously SQL Data Warehouse), Azure Storage Accounts (Data Lake) and / or Databricks.
· Analytical mind and business acumen
· Tableau, Power BI, strong math skills (e.g. statistics, algebra), Scala, Python or R.

Key Responsibilities:

· Identify valuable data sources and automate collection processes.
· Undertake pre-processing of structured and unstructured data.
· Analyze large amounts of information to discover trends and patterns.
· Data Modelling (Relational and Star Schema).
· Database design.
· Database development.
· Data Warehouse Design - Build and Development.
· Database Administration.
· Database Performance Tuning and Optimisation.
· Present information using data visualization techniques.
· Propose solutions and strategies to business challenges.
· Collaborate with engineering and product development teams.
· An understanding and hands on experience on Hadoop/Spark based distributed storage and computing frameworks.
· Real-Time analytics and batch processing.
· Strong experience in architecting analytical applications in cloud environment such as Amazon Web Services and Microsoft Azure.