Lead, Data Engineer

Standard Bank of South Africa Limited; Johannesburg; On-site; ZAR 600,000 - 800,000; Full time

Job summary

A leading banking institution in Johannesburg is seeking a Data Engineer to oversee junior data engineering activities, build data collection systems, and optimise the data pipeline architecture. The ideal candidate will have 8-10 years of experience with big data tools and data monetisation skills. Strong knowledge of SQL, cloud services, and data analytics is essential for this role.

Qualifications

• 8-10 years of experience in data monetisation and analytics.
• Experience with big data tools and cloud services.
• Working SQL knowledge and experience with relational databases.

Responsibilities

• Oversee junior data engineering activities.
• Build data collection systems and processing pipelines.
• Expand and optimise data and data pipeline architecture.

Skills

Data Monetisation

Data & Analytics

Big data tools (Hadoop, Spark, Kafka)

Relational SQL and NoSQL databases (Postgres, Cassandra)

Data pipeline and workflow management tools (Azkaban, Luigi, Airflow)

AWS cloud services (EC2, EMR, RDS, Redshift)

Stream-processing systems (Storm, Spark-Streaming)

Object-oriented/object function scripting languages (Python, Java, C++, Scala)

Education

Post Graduate Degree in Information Studies/Information Technology

Job description

Overview

Location: ZA, undefined, Johannesburg, 30 Baker Street

Responsible for overseeing junior data engineering activities and aiding in building the organisations data collection systems and processing pipelines. Oversee infrastructure, tools and frameworks used to support the delivery of end-to-end solutions to business problems through high performing data infrastructure. Responsible for expanding and optimising the organisations data and data pipeline architecture, whilst optimising data flow and collection to ultimately support data initiatives.

Responsibilities

Qualifications

• Type of Qualification: Post Graduate Degree
• Field of Study: Information Studies /Information Technology
• Experience Required
• Data Monetisation
• Data & Analytics
• 8-10 years
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• 8-10 years
• 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 \'big data\' data stores.
• 8-10 years
• Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing \'big data\' 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.