Mid Level Data Engineer Consultant

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- : Data Engineering on Microsoft Azure Certification.

Experience and Knowledge:

1. 5-8 years' working experience as a Data Engineer / Database Developer.
2. Experience in data mining, large scale data modelling and business requirements gathering / analysis.
3. Understanding and working experience in data integration and transformation.
4. Experience implementing data modelling methodologies like Dimensional Modeling and / or Data Vault.
5. Working knowledge of data quality processes and master data management.
6. Experience implementing design support systems using Database Management Systems (DBMS) such as SQL Server or Oracle.
7. Proficiency in designing and implementing data integration and ETL solutions using SSIS, Azure Data Factory and / or SQL Server stored procedures.
8. 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.
9. Experience in database query languages such as T-SQL, ANSI SQL, PL / SQL.
10. Some experience developing software solutions using Visual Basic, C++, C#, Java or Python.
11. Experience using SQL Server management Studio and Visual Studio.
12. Experience implementing solutions using Azure SQL databases, Azure Synapse (Previously SQL Data Warehouse), Azure Storage Accounts (Data Lake) and / or Databricks.

Key Responsibilities:

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

Competencies:

1. Critical Thinking: Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.
2. Active Learning: Understanding the implications of new information for both current and future problem-solving and decision-making.
3. Systems Analysis: Determining how a system should work and how changes in conditions, operations, and the environment will affect outcomes.
4. Complex Problem Solving: Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.
5. Deductive Reasoning: The ability to apply general rules to specific problems to produce answers that make sense.
6. Inductive Reasoning: The ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events).
7. 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.
8. 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.
9. Analytical Assessment: A high level of analysis to examine current systems and determine overall project needs and scope.
10. 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.
11. Team Leadership: To oversee and direct development teams throughout the project development lifecycle, experience with team leadership and motivation is essential.
12. Ability to translate strategy and strategic objectives into measurable and executable projects.
13. Experience working on large project(s) incorporating processes and procedures and standards.

Moyo Culture and Values: