Kearney Activate Senior Consultant Data Engineer

Kearney Italia, Inc.; Arlington (VA); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Competitive base compensation

Comprehensive medical, dental, and vision coverage

Flexible work and talent mobility programs

Job summary

A global consulting firm is seeking a Senior Consultant Data Engineer in Arlington, VA, to design, build, and maintain scalable data solutions. The ideal candidate should have strong experience in data engineering, proficiency in Python and SQL, and the ability to manage complex projects. You will lead technical work streams, mentor junior team members, and collaborate with clients to deliver impactful data solutions. This position offers competitive compensation, comprehensive benefits, and flexible work arrangements.

Qualifications

• Five or more years of experience in data engineering.
• Significant exposure to client-facing consulting environments.
• Demonstrated experience leading technical work streams.

Responsibilities

• Design and optimize data pipelines for large volumes of data.
• Develop ETL and ELT processes to integrate data sources.
• Collaborate with clients to understand data requirements.

Skills

Python

SQL

Data modeling techniques

Problem-solving skills

Communication skills

Education

Bachelor's degree in computer science or related field

Master's degree preferred

Tools

Databricks

AWS Glue

Azure Data Factory

Spark

Job description

Kearney Activate Senior Consultant Data Engineer

Full‑time Americas Arlington, VA, Boston, New York, Washington DC

Job Description

As a Senior Consultant Data Engineer, you will be a key contributor within Kearney Activate’s Solutions Architecture and Data Engineering practice. You will design, build, and maintain scalable data pipelines and infrastructure that support client data‑driven initiatives and enterprise transformations.

You will lead technical work streams, mentor junior team members, and collaborate closely with client stakeholders and cross‑functional teams to deliver high‑impact data solutions that enable advanced analytics, AI, and intelligent automation.

Key responsibilities

Design, implement, and optimize end‑to‑end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data across client environments.

Develop robust ETL and ELT processes to integrate data from diverse sources into modern data ecosystems, including data lakes, data warehouses, and cloud‑native platforms.

Implement data validationжал and quality checks to ensure accuracy, consistency, and reliability of data feeds.

Evaluate and implement streaming and real‑time data processing solutions where applicable.

Data modeling and architecture

Design and maintain data models, schemas, and database structures to support analytical, operational, and AI or ML use cases.

Optimize data storage and retrieval mechanisms for performance, scalability, and cost efficiency.

Evaluate and implement data storage solutions including relational databases, NoSQL databases, data lakes, data warehouses, and cloud storage services such as AWS S3, Azure Data Lake, Snowflake, and Databricks.

Contribute to the development of modern data architectures aligned with client business objectives and technical requirements.

Data integration and API development

Build and maintain integrations with internal and external data sources, APIs, and enterprise systems جائز

Implement RESTful APIs and web services for data access and consumption.

Ensure compatibility and interoperability across systems and platforms.

Design secure data exchange mechanisms that adhere to information security and compliance requirements.

Data infrastructure management

Configure and manage data infrastructure components, including databases, data warehouses, data lakes, and distributed computing frameworks such as Spark and Databricks.

Monitor system performance, troubleshoot issues, and implement optimizations to enhance reliability and efficiency.

Implement data security controls and access‑management policies to protect sensitive client information.

Leverage cloud platforms and services including AWS, Azure, and GCP to deploy and manage scalable data solutions.

Technical leadership and innovation

Act as technical lead on project work streams, providing guidance and oversight to junior data engineers and analysts.

Review code, data models, and technical designs toahami ensure adherence to best practices and standards.

Remove technical blockers and enable continuous progress across delivery teams.

Stay current with emerging technologies, including Gen AI capabilities, agentic architectures such as LangGraph and Agent Development Kit, Model Context Protocol, and automation frameworks.

Evaluate and implement intelligent automation and AI‑driven solutions where logically and practically applicable.

Contribute to internal knowledge repositories, reusable frameworks, and delivery accelerators.

Client engagement and collaboration

Collaborate directly with client technical and functional stakeholders to understand data requirements and deliver tailored solutions.

Partner with data scientists, analysts, architects, and business leaders to bridge technical execution and business outcomes.

Participate in client presentations and technical discussions, communicating complex concepts clearly and professionally.

Document technical designs, workflows, and best practices to support knowledge sharing and system maintenance.

Provide technical guidance and support to team members, clients, and stakeholders as needed.

Who you are

After nearly 100 years, we know this business is fundamentally about making connections between data, technology, strategy, and people. We look for curious, collaborative problem solvers who bring rigor to execution and thrive in fast‑paced, client‑facing environments.

We want to hear from you if you have:

Education and experience

A bachelor’s degree in computer science, engineering, information systems, or a related field, with a master’s degree preferred.

Five or more years of experience in data engineering, with significant exposure to client‑facing consulting or similar environments.

Demonstrated experience leading technical work streams and mentoring junior resources.

Technical skills

Proficiency in programming languages commonly used in data engineering, including Python and SQL, with Java or Scala a plus.

Strong knowledge of database systems, data modeling techniques, andchrist advanced SQL.

Hands‑on experience with ETL and ELT tools such as Databricks, Azure Data Factory, AWS Glue, Informatica Cloud, Talend, dbt, or Airflow.

Experience with big data technologies and frameworks including Spark, Hadoop, Kafka, and Kinesis.

Proven experience with cloud platforms and services such as Snowflake, AWS, and Azure, with Google Cloud Platform familiarity a plus.

Strong understanding of data warehousing concepts, dimensional modeling, and modern data architecture patterns.

Familiarity with GenAI applications in data engineering, agentic frameworks, and emerging technologies.

Excellent problem‑solving skills and attention to detail.

Strong communication skills with the ability to translate technical complexity for non‑technical stakeholders.

Ability to manage multiple concurrent projects and adapt to shifting priorities.

Self‑motivated with a drive to 섭 deliver highquality work and continuously improve.

A forward‑thinking approach to technology and curiosity about emerging trends and capabilities.

What we can offer you

Every day, our people work to make an impact for our clients, our colleagues, and our communities. At Kearney Activate, you will find competitive compensation, meaningful client work, and the opportunity to shape the future of data, AI, and enterprise transformation at scale.

We offer a comprehensive benefits package, including but not limited to:

Competitive base compensation with discretionary performance bonuses.

Comprehensive medical, dental, and vision coverage for employees and immediate family.

export retirement generous and savings contributions.

Non‑partner equity‑based awards for consulting managers and above.

Structured learning, technical growth, and leadership development opportunities.

Flexible work and talent mobility programs, including remote work options and externships.

Access to health, wellness, and family care benefits.

Read more about our benefits and careers at kearney.com/caremenes.

Equal Employment Opportunity and Non‑Discrimination Kearney prides itself on providing a culture that allows employees to bring their best selves to work every day. Our people can feel comfortable, confident, and joyful to do great things for our firm, our colleagues, and our clients. Kearney aims to build diverse capabilities to help our clients solve their most mission‑critical problems. Kearney is committed to building a diverse, unbiased, and inclusive workforce. KResource location; our company is an equal‑opportunity employer; we recruit, hire, train, promote, develop, and provide other conditions of employment without regard to a person’s gender identity or expression, sexual orientation, race, religion, age, national origin, disability, marital status, pregnancy status, veteran status, genetic information or any other differences consistent with applicable laws. This includes providing reasonable accommodation for disabilities, or religious beliefs and practices. Members of communities historically underrepresented in consulting are encouraged to apply.