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Buffalo, New York, United States
Hybrid
OVERVIEW:
Specializes in working with large and complex data sets to evaluate, recommend, and support the implementation of business strategies. Identifies and compiles data sets using a variety of tools to help predict, improve, and measure the success of key business-to-business outcomes. Mentoring junior analysts.
This role encompasses a comprehensive analysis lifecycle, covering requirements gathering, activity execution and design planning. Transforming raw data into structured information which will then be analyzed to glean insights that drive strategic business decisions.
POSITION RESPONSIBILITIES:
Identify the most authoritative sources of data and the most accurate data field(s) when domain data is sourced for internal projects and/or products by querying databases. Maintain advanced knowledge of domain's products and services, and an advanced understanding of how data supports those offerings.
Wrangle complex data sets using SQL or Python scripting for analysis and delivery purposes. Locate and explain data assets and connect them across different platforms and formats for multiple use cases.
Understand and document complex data flows for multiple business user stories, profile and review complex mappings and specifications across multiple use cases, develop enterprise level data solutions for problem statements, and perform complex data analysis across multiple use cases.
Prepare, create and execute large project, end to end test plans and scripts using SQL, Python, scripting and/or automation to test multiple/complex user stories.
Applies intermediate knowledge of their business domain including Business Operations, Business Processes, Data Flows and uses of Data in order to provide appropriate data to inform business decisions.
Mentor junior analysts in understanding M&T's data policies and procedures.
Translate business data needs into technical source-to-target mapping specifications and sample data mock-ups that provide clear direction to data engineers to enhance current data products in collaboration with stakeholders.
Conduct root-cause analysis of defects and triage these to the relevant teams for resolution depending on the root cause
Conduct impact analysis ahead of proposed business and/or technical changes
Communicate proposed data flows or source-to-target mappings along with their pros, cons, known limitations, variance materiality etc. to a variety of stakeholders, including business SMEs, product owners, data modelers, data engineers.
Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite. Identify risk-related issues needing escalation to management.
Promote an environment that supports diversity and reflects the M&T Bank brand.
Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.
Complete other related duties as assigned.
MINIMUM QUALIFICATIONS REQUIRED:
Bachelor’s degree and a minimum of 5 years related experience, or in lieu of a degree, a combined minimum of 9 years higher education and/ or work experience, including a minimum of 5 years related experience
Experience pulling data from Structured Query Language (SQL) platforms
Experience completing user acceptance testing for data products
Basic knowledge of data management
Knowledge of data cataloging and data lineage tools
Experience querying data that has been modeled in various techniques, e.g., slowly changing dimensions vs snapshots, key-value pairs vs normalized vs wide-table formats etc.
Experience developing source-to-target mappings in various data delivery patterns, e.g., full data loads vs CDC (change data capture) formats
IDEAL QUALIFICATIONS PREFERRED:
Experienced working as a member of an Agile Team
Experienced leading / mentoring team members on all analyst activities
Experience in creating data flows and high-level solutions with data
Advanced skills in SQL
Advanced knowledge of data management
Knowledge of assigned domain products, systems, and workflows
Data classification and privacy experience
Experienced using Data Governance Tools
Knowledge of statistic, data science techniques and tools
We support our team members with generous benefits.