The Data Engineer is accountable for developing high quality data products to support the
Bank’s regulatory requirements and data driven decision making. A Data Engineer will serve
as an example to other team members, work closely with customers, and remove or
escalate roadblocks. By applying their knowledge of data architecture standards, data
warehousing, data structures, and business intelligence they will contribute to business
outcomes on an agile team.
Responsibilities
• Developing and supporting scalable, extensible, and highly available data solutions
• Deliver on critical business priorities while ensuring alignment with the wider
architectural vision
• Identify and help address potential risks in the data supply chain
• Follow and contribute to technical standards
• Design and develop analytical data models
Required Qualifications & Work Experience
• First Class Degree in Engineering/Technology (4-year graduate course)
• 5 to 8 years’ experience implementing data-intensive solutions using agile
methodologies
• Experience of relational databases and using SQL for data querying, transformation
and manipulation
• Experience of modelling data for analytical consumers
• Ability to automate and streamline the build, test and deployment of data pipelines
• Experience in cloud native technologies and patterns
• A passion for learning new technologies, and a desire for personal growth, through
self-study, formal classes, or on-the-job training
• Excellent communication and problem-solving skills
Technical Skills (Must Have)
•
ETL:
Hands on experience of building data pipelines. Proficiency in two or more data
integration platforms such as Ab Initio, Apache Spark, Talend and Informatica
•
Big Data
: Experience of ‘big data’ platforms such as Hadoop, Hive or Snowflake for
data storage and processing
•
Data Warehousing & Database Management
: Understanding of Data
Warehousing concepts, Relational (Oracle, MSSQL, MySQL) and NoSQL (MongoDB,
DynamoDB) database design
•
Data Modeling & Design
: Good exposure to data modeling techniques; design,
optimization and maintenance of data models and data structures
•
Languages
: Proficient in one or more programming languages commonly used in
data engineering such as Python, Java or Scala
•
DevOps
: Exposure to concepts and enablers - CI/CD platforms, version control,
automated quality control management
Technical Skills (Valuable)
•
Ab Initio
: Experience developing Co>Op graphs; ability to tune for performance.
Demonstrable knowledge across full suite of Ab Initio toolsets e.g., GDE, Express>IT,
Data Profiler and Conduct>IT, Control>Center, Continuous>Flows
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