[FY26] Data Engineer – Industrials & Energy Sector – Senior Manager – Consulting – Location Open Position Available In Pulaski, Arkansas

[FY26] Data Engineer

• Industrials & Energy Sector
• Senior Manager
• Consulting
• Location Open
  at EY in Little Rock, Arkansas, United States
  Job Description

Location:

Anywhere in Country
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Technology

• Industrials & Energy Sector
• Data Engineering
• Senior Manager
  The opportunity
  EY is seeking a Senior Data Engineer to ingest, build, and support large-scale data architectures that serve multiple downstream systems and business users.

This individual supports the Data Engineer Leads and partners with Visualization on data quality and troubleshooting needs.
As a Senior Manager in Data Engineering, you will design and build analytics solutions that deliver significant business value. You will collaborate with a diverse team of data and analytics professionals, management, and stakeholders to ensure that our solutions meet business requirements. Your role will also involve understanding and translating business needs into technical requirements, ensuring that our development aligns with the intended design.
Your key responsibilities
In this role, you will be responsible for the effective management and delivery of complex processes and solutions. You will navigate operational dynamics while maintaining a focus on quality and risk management.

Your responsibilities will include:

Strategic Oversight:

Lead the strategic design and implementation of data engineering initiatives, ensuring alignment with business objectives and adherence to best practices in data architecture and ETL principles.

Cloud Solutions Leadership:

Oversee the design and maintenance of scalable data pipelines and architectures using cloud platforms such as AWS, Azure, and Databricks. Ensure solutions accommodate increasing data sources, volumes, and complexity.

Solution Recommendation:

Utilize your strong background to recommend and lead cloud-based and data engineering solutions, addressing complex technical challenges and ensuring optimal performance.

Pre-Sales and RFPs:

Engage in pre-sales activities and contribute to RFP responses by developing and articulating advanced data engineering solutions that address client needs and demonstrate the value of our offerings.

AI/ML and Advanced Analytics:

Collaborate with AI/ML engineers to design and implement data solutions that support machine learning, large language models (LLM), and advanced analytics. Integrate AI/ML capabilities into data engineering workflows.

Data Requirements and Validation:

Define data requirements, manage the ingestion of structured and unstructured data, and validate data using tools and methodologies in a Big Data environment.

Data Quality and Reconciliation:

Implement processes for data reconciliation and quality monitoring, ensuring production data is accurate and available for stakeholders, downstream systems, and business processes.

Technical Leadership:

Evaluate, implement, and deploy emerging tools and processes to enhance data engineering capabilities. Develop and deliver communication and education plans on data engineering standards and practices.

Digital and Cloud Modernization:

Lead digital transformation and cloud modernization efforts, leveraging cloud-native technologies and practices to improve data engineering solutions and processes.

Team Management:

Mentor and lead a team of data engineers, fostering a culture of innovation, continuous improvement, and professional development.

Stakeholder Collaboration:

Partner with Business Analytics, Solution Architects, Data Scientists, and AI/ML engineers to design and deliver data solutions that support advanced analytics, machine learning, and predictive modelling.
+ Leading engagement delivery and managing client relationships to achieve performance objectives.
+ Designing, building, and operating scalable data architecture and modeling solutions that support the entire data asset lifecycle.
+ Developing resource plans and budgets for engagements, ensuring alignment with performance metrics.
This position may require regular travel to meet with external clients, providing you with the opportunity to engage directly with stakeholders and drive impactful solutions.
Skills and attributes for success
To excel in this role, you will need a blend of technical and interpersonal skills. The following attributes will make a significant impact:
+ Strong analytical and decision-making skills to develop solutions to complex problems.
+ Ability to manage client relationships and navigate commercial dynamics effectively.
+ Proven leadership capabilities to guide teams and drive performance.

Cloud Solutions Expertise:

Strong background in designing and implementing cloud-based data solutions using AWS, Azure, Databricks, and other relevant cloud technologies.

AI/ML Integration:

Experience with AI/ML technologies, including machine learning, large language models (LLM), and integration of AI/ML capabilities into data engineering workflows.

Data Engineering Proficiency:

Extensive knowledge of data engineering principles, including building and optimizing data pipelines, and managing data architectures.

Technical Skills:

Proficiency in programming languages such as Python and Pyspark, and experience with distributed data technologies and API development.

Pre-Sales and Proposal Management:

Proven experience in pre-sales activities and contributing to RFP responses, with a track record of developing solutions that align with client requirements.

Leadership and Mentorship:

Demonstrated ability to lead and mentor teams, fostering a culture of collaboration, innovation, and professional growth.

Digital and Cloud Modernization:

Experience in leading digital transformation and cloud modernization initiatives, leveraging cloud-native technologies and practices.

Communication and Collaboration:

Excellent written and verbal communication skills, with the ability to interact effectively with multifunctional teams and strategic partners.

Problem Solving:

Strong problem-solving skills, with the ability to work in a dynamic environment and adapt to changing business priorities.
To qualify for the role, you must have
+ A Bachelor’s degree required; a Master’s degree preferred in Engineering, Computer Science, Data Science or a related field
+ Typically, no less than 8 years of relevant experience in data engineering, including significant experience in managing large-scale data projects and leading technical teams.
+ 5+ years of experience in the Manufacturing, Power & Utilities, Automotive, and/or Oil & Gas industries.
+ Proven track record of recommending and implementing complex data solutions, managing data pipelines and driving data quality and reconciliation
+ Experience with AWS, Azure, Databricks, Python, Pyspark, API development, and cloud modernization practices.
+ Strong organizational skills with the ability to manage multiple projects simultaneously and lead globally distributed teams.
+ Strong understanding of Cloud Computing
+ Proficiency in Data Architecture Design and Modelling
+ Expertise in Data Integration and Data Quality
+ Knowledge of Database Management and Data Security
+ Familiarity with Software Engineering principles
Ideally, you’ll also have
+ Experience leading teams and managing change effectively.
+ Strong negotiation and influencing skills.
+ A commitment to continuous learning and professional development.
+ A strong interest in applying emerging technologies to solve real-world data challenges
+ Ability to foster an inclusive environment that values diverse perspectives and empowers team members
What we look for
We seek individuals who are not only technically proficient but also p
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