Mid-Level Data Engineer

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.

• Proficiency in designing and implementing data integration and ETL solutions using SSIS, Azure Data Factory and / or SQL Server stored procedures.

• Understanding of several Big Data technologies like Hadoop, MapReduce and Spark as well as event processing or message ingestion services like Kafka, Event Hub and Stream Analytics.

• 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.

• Experience implementing solutions using Azure SQL databases, Azure Synapse (Previously SQL Data Warehouse), Azure Storage Accounts (Data Lake) and / or Databricks.

• Analytical mind and business acumen

• Additional skills in the following will be taken into consideration: 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 preprocessing 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.

Competencies:

• Critical Thinking: Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.

• Active Learning: Understanding the implications of new information for both current and future problem-solving and decision-making.

• Systems Analysis: Determining how a system should work and how changes in conditions, operations, and the environment will affect outcomes.

• Complex Problem Solving: Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.

• Deductive Reasoning: The ability to apply general rules to specific problems to produce answers that make sense.

• Inductive Reasoning: The ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events).

• Excellent communication skills: Ability to engage with C-level stakeholders, both verbal and non-verbal and communicate a deep understanding of the business and a broad knowledge of technology and applications.

• Technical Literacy: Possess a high level of technical literacy, which helps them determine how a software solution fits into an organization’s current structure and assists in the development of specifications and requirements.

• Analytical Assessment: A high level of analysis to examine current systems and determine overall project needs and scope.

• Schedule Management: Extensive time management skills to determine development schedules and milestones and ensure that deliverables are completed on time for oneself and your team.

• Team Leadership: To oversee and direct development teams throughout the project development lifecycle, experience with team leadership and motivation is essential.

• Ability to translate strategy and strategic objectives into measurable and executable projects.

• Experience working on large project(s) incorporating processes and procedures and standards