AWS Data Engineering Manager

SUMMARY: The Data Engineering Manager is someone who is passionate and motivated to make an impact in creating a robust and scalable data platform. This is a leadership role that provides a unique opportunity to create innovations and transformational change leveraging cloud and big data technologies. The position will provide architecture, design, development project management, and people leadership. The Data Engineering Manager will be responsible for managing the data engineering team as they build systems to support analytics, extend the Bank's data management platform, expand and optimize the Bank's data pipeline architecture, and work with Development teams to create cross-team solutions. The ideal candidate is an experienced data engineer with exposure to data wrangling practices and concepts who enjoys optimizing data systems and building them from the ground up. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The candidate will ideally have previous management experience with an engineering team and be excited by the prospect of optimizing or even re-designing, our company's data architecture to support our next generation of products and data initiatives. The candidate should also be comfortable with leading and designing projects initiatives that have both direct customer impact and backend impact for other Bank teams.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties and special projects may be assigned.

• Participate in the design and building of infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python, and AWS
• Collaborate with the Business Consumer product team and architecture group to help establish the customer data strategy
• Create and maintain optimal data pipeline architecture
• Focus on test driven design and results for repeatable and maintainable processes and tools
• Works with product and enterprise teams via both Agile and Waterfall Methodologies
• Lead teams optimizing ETL/ELT processes, developing data solutions and platforms to solve complex scenarios in an agile manner
• Build cross-functional relationships with Data Scientists, Product Managers, and Software Engineers to understand data needs and deliver on those needs
• Drive the design, building, and launching of new data models and data pipelines in production
• Manage the development of data resources and support new product launches
• Define and manage SLA's for all data sets and processes running in production.
• Drive architectural design patterns that focus on data security, data operational excellence, and optimization of data systems performance & cost efficiency
• Maintain current knowledge of cloud trends & developments and act as an advisor to the Bank in reference to its cloud strategies
• Contribute to the development of cloud standards, best practices and organizational cloud capability
• Develop and track staffing plans and ensures the team is adequately staffed with skilled professionals
• Leads recruitment efforts to attract, retain high quality and diverse talent
• Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
• Adheres to Bank policies and procedures and completes required training.
• Identifies and reports suspicious activity.

SUPERVISORY RESPONSIBILITIES

• Supervises function, projects or services and/or one or more employees, as applicable.
• Carries out supervisory responsibilities in accordance with the organization's policies and applicable laws.
• Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance coaching; rewarding and disciplining employees; addressing complaints and resolving problems.

EDUCATION

College degree or equivalent work experience (at least 10 years), which includes AWS and cloud data services experience.

EXPERIENCE

• Experience managing engineers and guiding a team of engineers through project planning, execution, and quality control stages
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience building data pipelines, architectures, and data sets from raw, loosely structured data
• Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management
• Proficiency with Data Warehouse and database platforms like Oracle, Redshift, and SQL is required
• Proficiency with Data Warehouse platforms such as Snowflake and BigQuery are a +
• Data Engineering experience using the following software/tools is preferred:
• Experience with relational SQL databases, including SQL, Postgres and MySQL
• Experience with object-oriented design in Python
• Experience with data pipeline and workflow management tools
• Experience with AWS cloud services: EC2, RDS, Redshift, Athena, EMR, Glue, S3
• Experience with Agile/Dev Ops methodologies and tools such as Jira and Confluence
• Multiple years experience with 3rd party vendor management
• Experience with access federation and identity management

CERTIFICATES, LICENSES, REGISTRATIONS

• AWS Certification is a plus

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