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CIBC US · 9 hours ago

Data Engineering Manager

Chicago, IL

Full-time

Hybrid

Mid, Senior Level

$150K/yr - $170K/yr

5+ years exp

CIBC US is building a relationship-oriented bank for the modern world, seeking talented professionals. The Data Engineering Manager will lead a team to deliver data solutions, oversee ETL processes, and ensure high-quality code while fostering collaboration across functions.

BankingFinancial Services

No H1B

Responsibilities

Own delivery for Data ETL, analytics and consumption capabilities in alignment with a multi-year Product Roadmap

Work across functions – Product, Architecture, Data, Stakeholders - to understand business/design/Product objectives, then build solutions, whether internal or external

Stay ahead of changing technologies and demonstrate experience with clean interfaces and data strategy

Lead and inspire development team of 8-10 technology professionals including developers, testers, and analysts to solve complex data modeling, transformation, and consumption solutions

Oversee the development, testing and implementation of Data Solutions including ETL, Analytics, Data Quality and Lineage in a secure cloud environment

Hold teams accountable for quality of code, and achieving committed work within a sprint, release, or roadmap

Lead code reviews to ensure best practice coding processes

Mentor developers on improvements

Define and manage resource requirements and allocations, monitor and improve quality, and ensure 'best practice' development techniques

Create better ways of solving technical problems and not be afraid of challenging the status quo and work to plan releases and release schedules

Manage intake process for application project estimates, identify bottlenecks across SDLC, evaluate performance opportunities, and implement and manage Key Performance Indicators

Successfully execute Agile Scrum practices including capacity estimation, story pointing, measuring/monitoring velocity, and leveraging ceremonies and practices accordingly

Develop proofs of concept (POC) as needed to evaluate product and technical strategies

Facilitate brainstorming sessions, build consensus, and shepherd solutions through governance forums

Qualification

Data EngineeringETLAzure SQLPySparkScalaDatabricksData ArchitectureData QualityAgile MethodologyAnalytical ThinkingPeople ManagementCommunicationProject ManagementTechnical Leadership

Required

5+ years of experience as a Development Lead on Data Applications

Strong Data infrastructure and Data Architecture skills

Solid proficiency in the Data technology stack, including but not limited to PySpark, Scala, Databricks, ETL, Azure SQL and REST APIs

Exposure to Integration and BI Tools such as Tableau, Cognos or Power BI

Expertise in data ingestions, data pipeline development, and optimization, reporting, and advanced analytics using Azure and Databricks (Pyspark/Scala) services

Knowledge of approaches, tools, techniques and roles and responsibilities in providing technical or business guidance to business and technical partners

Significant automation experience for minimizing manual processes

Solid understanding of cloud technologies and tools

Expert communications with c-suite and key technical partners for development tollgates and governance forums

Ability to document and tell a ‘story' for a technical recommendation from framework to feature level

Outstanding DevOps practices for environment management and integrity, security, pipeline management, code integrity, compliance, release management

Solid execution of practices for Jira/Azure DevOps Taxonomies, Story Writing, Story Pointing, Velocity measurement

Strong operational skills to drive efficiency and speed

Strong project management leadership

Proven track record of leading and scaling Data Engineering teams

Critical thinking skills to inform decision-making