Data Engineer

SUMMARY:
The Role:

We are searching for committed and dynamic Data Engineer for the Banking sector in their Information Technology Division, focusing on systems development, business analysis, architecture, project management, data warehousing, infrastructure, maintenance and production.

Provide infrastructure, tools and frameworks used to delive...

POSITION INFO:
The Role:

We are searching for committed and dynamic Data Engineer for the Banking sector in their Information Technology Division, focusing on systems development, business analysis, architecture, project management, data warehousing, infrastructure, maintenance and production.

Provide infrastructure, tools and frameworks used to deliver end-to-end solutions to business problems. Build scalable infrastructure for supporting the delivery of clear business insights from raw data as well as curated sources; with a focus on collecting, managing, analyzing, visualizing data and developing analytical solutions.

Responsible for expanding and optimizing Bank''s data and data pipeline architecture, whilst optimizing data flow and collection to ultimately support data initiatives. 

Essential Skills:

• 3 -4 years experience in Data Monetisation - Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases; and  Experience building and optimizing â??big dataâ?? data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• 3 -4 years experience in Data Monetisation -  Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable â??big dataâ?? data stores.
• 3 -4 years experience in Data Monetisation - Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, such as Redshift and DynamoDB. Experience with data pipeline and workflow management tools: AWS Data Pipeline, AWS Glue, etc. Experience with stream-processing systems: Kafka, Spark-Streaming, etc. Experience with object-oriented/object function scripting languages: Python, Java, C#, Scala, etc. Experience with exposing data via APIs. Experience with AWS DevOps tools such as CodeBuild, CodePipeline, CodeDeploy; and Experience with containerirsation technologies such as Docker.

Essential Qualifications:

• Degree in Information Technology + AWS Certified

 

AWS Certifications required:

• AWS Certified Data Analytics Specialty
• AWS Certified Developer Associate
• AWS Certified DevOps Engineer Professional

Key Performance Areas:

Data Functions:

• Create and maintain optimal data pipeline architecture and creating databases optimized for performance, implementing schema changes, and maintaining data architecture standards across the required Standard Bank databases. Work alongside data scientists to help make use of the data they collect.
• Assemble large, complex data sets that meet functional / non-functional business requirements and align data architecture with business requirements. Processes, cleanses, and verifies the integrity of data used for analysis.
• Data Responsible for enabling and running data migrations across different databases and different servers and defines and implements data stores based on system requirements and consumer requirements.
• Responsible for performing thorough testing and validation in order to support the accuracy of data transformations and data verification used in machine learning models.
• Perform ad-hoc analyses of data stored in Standard Banks databases and writes SQL scripts, stored procedures, functions, and views. Proactively analyses and evaluates the Standard Banks databases in order to identify and recommend improvements and optimisation. Deploy sophisticated analytics programs, machine learning and statistical methods.
• Analyse complex data elements and systems, data flow, dependencies, and relationships in order to contribute to conceptual physical and logical data models.

Product functions:

• Build analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Create data tools for analytics and data scientist team members that assist them in building and optimising Standard Bank into an innovative industry leader.
• Utilise data to discover tasks that can be automated and identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Designing and developing scalable ETL packages from the business source systems and the development of ETL routines in order to populate databases from sources and to create aggregates. Oversee large-scale data Hadoop platforms and to support the fast-growing data within the business.

People Functions:

• Liaise and collaborate with the entire EDO team, providing support to the entire department for its data centric needs. Collaborate with subject matter experts to select the relevant sources of information and translates the business requirements into data mining/science outcomes. Presents findings and observations to team for development of recommendations.
• Acts as a subject matter expert from a data perspective and provides input into all decisions relating to data engineering and the use thereof. Educate the organisation on data engineering perspectives on new approaches, such as testing hypotheses and statistical validation of results. Ensure ongoing knowledge of industry standards as well as best practice and identify gaps between these definitions/data elements and company data elements/definitions.

Personality Traits:

• Analytical
• Problem solver
• Passion for new technologies
• Team Player but self-driven
• Good communication - written and verbal

 

 

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