The RoleThe Data Engineer is accountable for developing high quality data products to support theBank’s regulatory requirements and data driven decision making. A Data Engineer will serveas an example to other team members, work closely with customers, and remove orescalate roadblocks. By applying their knowledge of data architecture standards, datawarehousing, data structures, and business intelligence they will contribute to businessoutcomes 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 widerarchitectural vision• Identify and help address potential risks in the data supply chain• Follow and contribute to technical standards• Design and develop analytical data modelsRequired Qualifications & Work Experience• First Class Degree in Engineering/Technology (4-year graduate course)• 9 to 11 years’ experience implementing data-intensive solutions using agilemethodologies• Experience of relational databases and using SQL for data querying, transformationand 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, throughself-study, formal classes, or on-the-job training• Excellent communication and problem-solving skills• An inclination to mentor; an ability to lead and deliver medium sized componentsindependentlyTechnical Skills (Must Have)•
ETL:Hands on experience of building data pipelines. Proficiency in two or more dataintegration platforms such as Ab Initio, Apache Spark, Talend and Informatica•Big Data: Experience of ‘big data’ platforms such as Hadoop, Hive or Snowflake fordata storage and processing•Data Warehousing & Database Management: Expertise around DataWarehousing 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 indata engineering such as Python, Java or Scala•DevOps: Exposure to concepts and enablers - CI/CD platforms, version control,automated quality control management•Data Governance:A strong grasp ofprinciples and practice including data quality,security, privacy and complianceTechnical 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•Cloud: Good exposure to public cloud data platforms such as S3, Snowflake,Redshift, Databricks, BigQuery, etc. Demonstratable understanding of underlyingarchitectures and trade-offs•Data Quality & Controls: Exposure to data validation, cleansing, enrichment anddata controls•Containerization: Fair understanding of containerization platforms like Docker,Kubernetes•File Formats:Exposure in working on Event/File/Table Formats such as Avro,Parquet, Protobuf, Iceberg, Delta•Others:Experience of using a Job scheduler e.g., Autosys. Exposure to BusinessIntelligence tools e.g., Tableau, Power BICertification on any one or more of the above topics would be an advantage.
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Job Family Group:
Technology
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Job Family:
Digital Software Engineering
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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