Kearney Activate Senior Consultant Data Engineer

Kearney; Boston (MA); On-site; USD 100,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits package

Flexible work options

Job summary

Kearney seeks a Senior Consultant Data Engineer in Boston, MA, to lead data engineering efforts and develop scalable solutions. You will mentor junior engineers and work closely with clients to deliver impactful data-driven transformations.

Candidates should have significant experience in data engineering, excellent problem-solving and communication skills, and a proven track record in managing technical projects. A competitive compensation range is offered.

Qualifications

• 5+ years of experience in data engineering.
• Experience in leading technical work streams.
• Ability to guide and mentor junior team members.

Responsibilities

• Design and optimize end-to-end data pipelines.
• Maintain data models and schemas for analytics.
• Collaborate with stakeholders to meet data requirements.

Skills

Proficiency in Python

Strong SQL knowledge

Experience with ETL tools

Familiarity with cloud platforms

Excellent problem-solving skills

Strong communication skills

Education

Bachelor's degree in computer science or related field

Master's degree preferred

Tools

Databricks

AWS

Azure

Spark

Kafka

Job description

Job Description

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

Data Pipeline Development

• 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 validation 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.
• 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 to 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; 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; Java or Scala a plus.
• Strong knowledge of database systems, data modeling techniques, and 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; familiarity with Google Cloud Platform 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.

Professional Competencies

• Excellent problem‑solving skills and attention to detail.
• Strong communication skills, with the ability to translate technical complexity for non‑technical stakeholders.
• Effective collaboration skills in cross‑functional, team‑oriented environments.
• Ability to manage multiple concurrent projects and adapt to shifting priorities.
• Self‑motivated with a drive to deliver high‑quality work and continuously improve.
• A forward‑thinking approach to technology and curiosity about emerging trends and capabilities.

Security Clearance Requirement (or ability to obtain): Secret

This position requires an active Secret security clearance or the ability to obtain one. A Secret clearance is a U.S. government security clearance that allows access to classified national security information that could cause serious damage to national security if disclosed without authorization.

Key Points

• Issued by the federal government after a background investigation.
• Requires U.S. citizenship.
• Involves investigation into criminal history, financial records, and personal conduct.
• Must be sponsored by a government agency or cleared defense contractor.
• Requires periodic reinvestigation (typically every 10 years).
• Clearance processing typically takes 3–6 months but can vary.

Candidates must be able to meet the eligibility requirements established by the U.S. government for access to classified information at the Secret level.

What We Can Offer You

• Competitive compensation, meaningful client work, and the opportunity to shape the future of data, AI, and enterprise transformation at scale.
• 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, generous retirement 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, and access to health, wellness, and family care benefits.
• Additional benefits include paid time off, 401(k) match and profit sharing, medical, dental and vision coverage, healthcare concierge, backup child/adult care, annual employer HSA contribution, home office stipend, subsidized Gympass and annual wellness program, and leaves of absence when needed to support employees’ physical, mental, and emotional well‑being.

Compensation Range

$100k–$160k. It is important to note that at Kearney, it is not typical for an individual to be hired at the top of the range for their role. Individual salaries within each range are determined through a wide variety of factors including but not limited to education, experience, knowledge and skills. Kearney reviews compensation regularly and may adjust base salaries to reflect market competitiveness. In addition to salary, individuals may be eligible for a discretionary performance bonus.

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. Kearney 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.