Senior HR Data Engineer

Bank of Montreal•Chicago, IL

13h

About The Position

Oversees the development of methods, practices, policies, tools and processes to collect, store, access and use data securely, efficiently, and cost-effectively. Supports the full lifecycle of data assets. Assures the quality of data collection, including the adequacy, accuracy and legitimacy of the data. Identifies ways to manage data across a diverse but unified data tier. Plans and supports the implementation of cloud data management platforms and tools, policies and procedures giving the organization control of business data, both in cloud applications and hybrid cloud/ on-premise set-ups. Manages data integration applying relevant data governance and management practices. Creates and maintains an optimal data pipeline architecture. Assembles large, complex data sets that meet functional / non-functional business requirements. Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability. Builds the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources. Builds analytics tools that utilize the data pipeline to provide actionable insights into customer, operational efficiency and other key business performance metrics. Works with different stakeholders and teams to assist with data-related technical issues and support their data infrastructure needs. Works with experts in data strategy and data governance to suggest quality enhancements. Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus. Provides specialized consulting, analytical and technical support. Exercises judgment to identify, diagnose, and solve problems within given rules. Works independently and regularly handles non-routine situations. Broader work or accountabilities may be assigned as needed. Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.

Requirements

Foundational level of proficiency: Creative thinking.
Intermediate level of proficiency: Data architecture design and modeling. Cloud computing architecture. Data security. Machine learning. Computational thinking and programming. Deep learning. Decision making. Critical thinking. Verbal & written communication skills. Collaboration & team skills. Analytical and problem solving skills. Data driven decision making.
Advanced level of proficiency: Data integration. Data warehousing. Enterprise data management. Data mining. Big data. Streaming / Real time.
Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
Deep knowledge and technical proficiency gained through extensive education and business experience.

Responsibilities

Oversees the development of methods, practices, policies, tools and processes to collect, store, access and use data securely, efficiently, and cost-effectively.
Supports the full lifecycle of data assets.
Assures the quality of data collection, including the adequacy, accuracy and legitimacy of the data.
Identifies ways to manage data across a diverse but unified data tier.
Plans and supports the implementation of cloud data management platforms and tools, policies and procedures giving the organization control of business data, both in cloud applications and hybrid cloud/ on-premise set-ups.
Manages data integration applying relevant data governance and management practices.
Creates and maintains an optimal data pipeline architecture.
Assembles large, complex data sets that meet functional / non-functional business requirements.
Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
Builds the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
Builds analytics tools that utilize the data pipeline to provide actionable insights into customer, operational efficiency and other key business performance metrics.
Works with different stakeholders and teams to assist with data-related technical issues and support their data infrastructure needs.
Works with experts in data strategy and data governance to suggest quality enhancements.
Provides specialized consulting, analytical and technical support.
Exercises judgment to identify, diagnose, and solve problems within given rules.
Works independently and regularly handles non-routine situations.
Broader work or accountabilities may be assigned as needed.
Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.