AI / Data Engineer 4 – Comcast Global Audit

Comcast•Philadelphia, PA

16h•Hybrid

About The Position

Comcast brings together the best in media and technology, driving innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, Comcast sets the pace in innovative businesses and creates career opportunities across various locations and disciplines. The AI / Data Engineer (Level 4) plays a critical role in driving best practices supporting Comcast Global Audit (CGA) by building, supporting, and maintaining a modern audit data platform for advanced data analytics, automation, and artificial intelligence. This role focuses on designing scalable, resilient data pipelines and AI solutions with a strong emphasis on automation, quality, governance, and observability. The ideal candidate brings deep technical expertise, strong system thinking, and the ability to lead technical decisions that drive scalability, trust, and transparency across the audit data ecosystem. This position offers broad exposure to the Comcast Corporation through the audit process and provides opportunities to influence risk management strategies through data-driven insights.

Requirements

Deep technical expertise and strong system thinking.
Ability to lead technical decisions that drive scalability, trust, and transparency across the audit data ecosystem.
Solid project management skills for data or automation related projects.
Experience designing, building, and maintaining resilient, automated data pipelines and AI solutions.
Experience implementing modular, well-documented transformation logic and data models.
Experience with data quality checks and observability tooling (e.g., Monte Carlo, Great Expectations).
Experience building end-to-end pipeline monitoring: logging, alerting, and traceability.
Experience developing and supporting CI/CD pipelines (e.g., GitHub Actions) for secure, auditable deployments.
Experience managing data integration across diverse sources (APIs, SFTP, databases) using secure, repeatable patterns with version control and infrastructure-as-code practices.
Ability to independently deliver robust engineering solutions, including root-cause analysis and long-term fixes.
Ability to lead code reviews and contribute to team-wide engineering standards, documentation, and architecture.
Strong operational rigor in writing testable, observable, well-documented code that scales.
Ability to engage in collaborative planning and sprint cycles with cross-functional data teams.
Knowledge of data security and company policies regarding data classification.
Ability to analyze data to assess compliance with established policies/procedures, best practices, US GAAP, and legal/governmental requirements.
Proficiency in data concepts, tools, and programming techniques including SQL, dbt, Snowflake, Airflow, Tableau, AWS, MS SQL Server, Oracle BI, Teradata, Databricks, Alteryx, Spark, Python, and R.
Experience using AI technologies and building solutions using MS CoPilot, GitHub CoPilot, Azure, ChatGPT, etc.
Ability to develop process flows, prototypes, and requirements documentation.
Ability to create, document, and execute support process steps and test procedures.
Ability to facilitate discussions that lead to decision-making throughout the lifecycle of creating and enhancing data solutions.
Ability to prepare clear and well-organized analysis workpapers, documenting root-cause, work performed, findings, and recommendations.
Ability to create graphical reports and executive presentations.
Accountability for and ability to review team workpapers, presentations, and other documentation.
Consistently exercises independent judgment and discretion in matters of significance.
Ability to assist with managing, scheduling, monitoring, and maintaining automated processes in production.
Ability to quickly grasp complex subject matter and apply strong analytical skills and business knowledge.
Ability to stay current on data analytics trends, data engineering, and emerging technologies (e.g., AI, Blockchain, RPA).
Commitment to continuously explore and evaluate new tools, libraries, and frameworks.
Ability to perform effectively as a project leader.
Flexibility in prioritizing and completing tasks, and allocating/re-allocating work.
Ability to work with discretion applying sound judgment.
Utilizes creative thinking, individual initiative, and flexibility.
Willingness to tackle new areas and challenging topics.
Ability to work in a complex, dynamic, and fast-paced environment.
Strong interpersonal skills including written and verbal communications, and an ability to collaborate with others.
Willingness to assist other team members in areas outside of direct assignments.
Ability to collaborate in a virtual environment.
Ability to supervise engagement staff member’s interactions with business management.
Ability to engage and build collaborative relationships with key business partners, other risk functions, and system owners.
Ability to coach audit team members on data analytics, automation techniques, and business knowledge.
Ability to assist engagement team in developing their understanding of relevant business risks and train them.
Commitment to continuously self-improve.
Knowledge of IT controls and cyber security concepts.
Ability to manage and mentor engagement team members.
Bachelor's Degree (or some combination of coursework and experience, or extensive related professional experience).
7-10 Years Relevant Work Experience.
Regular, consistent, and punctual attendance.
Ability to work nights and weekends, variable schedule(s), as necessary.
Ability to travel out-of-town up to approximately 20%.

Responsibilities

Build, support, and maintain a modern audit data platform for advanced data analytics, automation, and artificial intelligence within Comcast Global Audit (CGA).
Design scalable, resilient data pipelines and AI solutions with a focus on automation, quality, governance, and observability.
Lead technical decisions to drive scalability, trust, and transparency across the audit data ecosystem.
Transform fragmented, manual data inputs into production-grade pipelines supporting audit engagements across Comcast’s business units.
Support and provide feedback in the design of scalable data solutions that support audit objectives.
Oversee other team members in driving consistency across the data ecosystem.
Proactively identify improvement areas for standardization and automation, leveraging artificial intelligence and strategically aligning with audit senior leaders.
Demonstrate solid project management skills for data or automation related projects, including developing project plans and budgets, scheduling deliverables, executing per plan, and messaging status/issues to management.
Implement modular, well-documented transformation logic and data models to support standardized audit workflows.
Introduce and maintain data quality checks and observability tooling (e.g., Monte Carlo, Great Expectations) to ensure data accuracy, lineage, and pipeline reliability.
Build end-to-end pipeline monitoring: logging, alerting, and traceability from source ingestion to report-ready datasets.
Develop and support CI/CD pipelines (e.g., GitHub Actions) for secure, auditable deployments of infrastructure and code.
Manage data integration across diverse sources (APIs, SFTP, databases) using secure, repeatable patterns with version control and infrastructure-as-code practices.
Independently deliver robust engineering solutions with minimal supervision, including root-cause analysis and long-term fixes for data pipeline issues.
Lead code reviews and contribute to evolving team-wide engineering standards, documentation, and architecture, championing best practices.
Deliver incremental benefits with tangible deliverables balancing short-term audit needs with long-term architectural improvements that reduce technical debt and manual effort.
Maintain strong operational rigor such as writing testable, observable, well-documented code that scales across engagements.
Engage in collaborative planning and sprint cycles with cross-functional data teams to align on scope, milestones, and blockers.
Ensure all data is secure and follows company policies regarding data classification.
Analyze data to assess compliance with established policies/procedures, best practices, US GAAP, and legal/governmental requirements.
Use data concepts, tools, and programming techniques including SQL, dbt, Snowflake, Airflow, Tableau, AWS, MS SQL Server, Oracle BI, Teradata, Databricks, Alteryx, Spark, Python, and R to perform ETL and data analysis activities.
Use AI technologies and build solutions using MS CoPilot, GitHub CoPilot, Azure, ChatGPT, etc.
Develop process flows, prototypes, and requirements documentation to accelerate stakeholder understanding and guide solution development.
Create, document, and execute support process steps and test procedures to ensure data deliverables are accurate and sustainable.
Facilitate discussions that lead to decision-making throughout the lifecycle of creating and enhancing data solutions.
Prepare clear and well-organized analysis workpapers, documenting root-cause (as applicable), work performed, findings, and recommendations.
Create graphical reports and executive presentations to effectively summarize analysis and findings.
Be accountable for and review team workpapers, presentations, and other documentation to ensure they are clear, complete, and well-organized.
Consistently exercise independent judgment and discretion in matters of significance.
Assist with managing, scheduling, monitoring, and maintaining automated processes in production.
Support department objectives and perform other duties and responsibilities, as assigned.
Quickly grasp complex subject matter and apply strong analytical skills and business knowledge to assessing processes, risks, and controls.
Stay current on data analytics trends (e.g., new tools, statistical methods, visualization techniques), data engineering (e.g., orchestration, observability, step functions, cloud patterns, data governance) and emerging technologies that impact audit work (e.g., AI, Blockchain, RPA).
Continuously explore and evaluate new tools, libraries, and frameworks relevant to data quality, automation, and audit transparency.
Perform effectively as a project leader across engagements.
Show flexibility in prioritizing and completing tasks, allocating/re-allocating work across engagement team members, or stepping in to support execution, as appropriate.
Work with discretion applying sound judgment regarding work details on assignments of a varied and difficult nature while maintaining personal and broader team accountability and ownership.
Utilize creative thinking, individual initiative, and flexibility in prioritizing and completing tasks.
Exhibit willingness to tackle new areas and challenging topics.
Work in a complex, dynamic, and fast-paced environment.
Assist less experienced team members in understanding and executing data analytics and automation activities.
Provide ongoing feedback and follow-up to less experienced team members on work completion and performance, as well as ensuring timely delivery of data deliverables for audit engagements.
Assist less experienced team members in ensuring data deliverables supporting audit engagements are designed with shared logic and developed consistent, accurate, and scalable.
Provide coaching, guidance, and development on interactions with business management and stakeholders.
Identify opportunities for improvement to team activities, tools, and training.
Transparently keep CGA management informed of findings / status / important issues as they arise.
Act in accordance with stated CGA and company policies and practices, and maintain the highest degree of integrity in all activities and interactions.
Display regular, consistent, and punctual attendance.
Be able to work nights and weekends, variable schedule(s), as necessary.
Travel out-of-town may be required at up to approximately 20%.
Collaborate with members of CGA engagement teams to understand audit activities and identify ways that data analytics and/or automation can enhance overall work product, productivity, or audit coverage.
Partner strategically with members of audit senior leadership across engagement activities, understanding their perspectives, and proposing / discussing solutions that manage risk and optimize team resources.
Exhibit strong interpersonal skills including written and verbal communications, and an ability to collaborate with others.
Show respect to other team members and clients in all interactions.
Demonstrate a willingness to assist other team members in areas outside of direct assignments, when necessary.
Collaborate in a virtual environment to complete projects with team members in various locations.
Supervise engagement staff member’s interactions with business management and helps team members to resolve issues.
Engage and build collaborative relationships with key business partners, other risk functions, and system owners (e.g., Legal, Human Resources, Security, TPX, EBI, etc.), as needed.
Coach audit team members on data analytics, automation techniques, and business knowledge.
Assist engagement team in developing their understanding of relevant business risks and trains team on how to consider when planning and executing engagements.
Utilize available resources and tools to research and expand knowledge to enhance work product.
Exhibit a commitment to continuously self-improve by working with leadership to leverage strengths and focus on areas of development.
Gain knowledge of IT controls and cyber security concepts and actively apply to engagements.
Manage and mentor engagement team members to develop audit, data, and business knowledge.
Assist less experienced team members with furthering their own development.