Data Engineering Lead

17 hours ago


Jersey City, New Jersey, United States Royal Bank of Canada Full time
Job Summary

Royal Bank of Canada seeks a highly skilled Data Engineering Lead to support the development and maintenance of scalable data stores. The ideal candidate will have expertise in designing and developing metadata frameworks for ingestion, profiling, anomaly detection, and data repairs. Additionally, they will have experience with designing data distributed computing engines, including Spark, for scalable and efficient profiling of alternative data. The successful candidate will also have a strong background in developing auditable data repair frameworks for imputation and repair of missing and incorrect data. Furthermore, they will have experience with engineering ML Ops frameworks to ensure immutability and reproducibility of models within the Data Engineering workspace. The Data Engineering Lead will also be responsible for building pipelines to collect data from external and internal data sources. The role requires a Bachelor's degree in Computer Science, Data Engineering, or a related technical field, plus 7 years of progressively responsible experience, or a Master's degree in Computer Science, Data Engineering, or a related technical field, plus 3 years of experience. The ideal candidate will have experience with financial industry experience using Azure, Airflow, Python, PySpark, Scala, and shell scripting; AI, Big Data, Cloud, distributed computing, alternative data, and data science; building metadata-driven AI and statistical models; and experience with KPIs and backtesting of alternative data factors. The salary range for this role is $169,000 - $225,000, which includes a discretionary bonus and benefits such as a 401(k) program with company-matching contributions; health, dental, vision, life, and disability insurance; and paid time-off plan. RBC's compensation philosophy and principles recognize the importance of a highly qualified global workforce and play a critical role in attracting, engaging, and retaining talent that drives RBC's high-performance culture, enables collective achievement of our strategic goals, and generates sustainable shareholder returns and above-market shareholder value.

Key Responsibilities
  • Design and develop metadata frameworks for ingestion, profiling, anomaly detection, and data repairs.
  • Design data distributed computing engines, including Spark, for scalable and efficient profiling of alternative data.
  • Develop auditable data repair frameworks for imputation and repair of missing and incorrect data.
  • Engineer ML Ops frameworks to ensure immutability and reproducibility of models within the Data Engineering workspace.
  • Build pipelines to collect data from external and internal data sources.

Requirements
  • Bachelor's degree in Computer Science, Data Engineering, or a related technical field, plus 7 years of progressively responsible experience.
  • Or Master's degree in Computer Science, Data Engineering, or a related technical field, plus 3 years of experience.
  • Financial industry experience using Azure, Airflow, Python, PySpark, Scala, and shell scripting.
  • AI, Big Data, Cloud, distributed computing, alternative data, and data science.
  • Building metadata-driven AI and statistical models.
  • Experience with KPIs and backtesting of alternative data factors.

What We Offer
  • Salary range: $169,000 - $225,000.
  • Discretionary bonus.
  • Benefits: 401(k) program with company-matching contributions; health, dental, vision, life, and disability insurance; and paid time-off plan.

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