Role: Data Engineer
Duration: 6 Months
Location : Toronto
- Champions a customer focused culture to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
- Conduct ETL, SQL and DB performance tuning, troubleshooting, support, and capacity estimation to ensure highest data quality standards.
- Profiles data and ETL logic for documenting end to end data flow and lineage from capture at source, to storage, to delivery and its business intent at each stage (i.e. capture, transformation, fragmentation, editing)
- Profile and analyze source data to determine the best reporting structures to build.
- Design and develop ETL pipelines using multiple sources of data in various formats according to business requirements.
- Conduct dimensional modelling, metadata management, data cleaning and conforming, and warehouse querying.
- Use sound agile development practices (code reviews, testing, etc) to develop and deliver data products
- Provide day-to-day support and technical expertise to both technical and non-technical teams
- Work with other engineers to brainstorm solutions to problems and support others in their goals.
- Exhibit sound judgement, keen eye for details and tenacity for solving difficult problems.
- Use strong analytical skills and support use of data for sound decision making.
- Help us build data expertise and data focused mindset throughout the enterprise
- Translate business needs into technical requirements
- Understand how the Bank’s risk appetite and risk culture should be considered in day-to-day activities and decisions.
- Actively pursues effective and efficient operations of his/her respective areas, while ensuring the adequacy, adherence to and effectiveness of day-to-day business controls to meet obligations with respect to operational risk, regulatory compliance risk, AML/ATF risk and conduct risk, including but not limited to responsibilities under the Operational Risk Management Framework, Regulatory Compliance Risk Management Framework, AML/ATF Global Handbook and the Guidelines for Business Conduct.
- Champions a high performance environment and contributes to an inclusive work environment.
- Degree in Engineering, Computer Science or Mathematics/Statistics.
- 5+ years industry experience with big data technology (Hadoop, Hive, Spark, SQL, Kafka, etc.)
- Industry experience as a Data Engineer
- Data modelling and warehousing experience
- Proficiency with relational databases (Oracle, DB2, Redshift, etc.)
- Strong proficiency in SQL
- API development experience
- Experience working in an Agile team environment