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Clarkston Consulting

Consumer products and life sciences consulting

Data Engineering Senior Consultant

Data EngineeringConfirmed live in the last 24 hours
Full-timeDallas, TX, USANo salary listed

About the Job

Requirements

  • Experience assembling large, complex data sets that meet functional and non-functional business requirements.
  • Experience designing and implementing scalable data architectures, pipelines, and data solutions.
  • Experience applying data modeling concepts to create schemas, including star and snowflake schemas, based on business and analytical requirements.
  • Experience working with stakeholders to understand business needs and translate them into data and technical solutions.
  • Ability to communicate recommendations, findings, and technical concepts effectively with client stakeholders and project teams.
  • Experience identifying and implementing internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for scalability.
  • Experience leveraging appropriate infrastructure to extract, transform, and load data from diverse sources using SQL and big data technologies.
  • Experience building analytics tools and data solutions that provide actionable insights into customer acquisition, operational efficiency, and other business performance metrics.
  • Experience working with cross-functional Product, Data, Design, and business stakeholders to address data-related technical issues and support data infrastructure needs.
  • Experience in a consulting environment involving collaboration, problem-solving, adaptability, and client service.
  • Experience working directly with clients, including leading discussions, facilitating requirements sessions, presenting recommendations, and building trusted working relationships.
  • Experience applying consulting skills including structured problem-solving, requirements gathering, communication, project collaboration, and managing multiple priorities.
  • At least 3 years of experience in a Data Engineer or related data-focused role.
  • Advanced SQL knowledge, including relational databases and query authoring, and familiarity with a variety of databases.
  • Experience building and optimizing big data pipelines, architectures, and data sets.
  • Experience with data modeling and schema design, including star and snowflake schemas.
  • Experience performing root cause analysis on internal and external data and processes to answer business questions and identify opportunities for improvement.
  • Strong analytical skills for working with structured and unstructured datasets.
  • Experience building processes that support data transformation, data structures, metadata, dependency, and workload management.
  • A successful history of manipulating, processing, and extracting value from large and disconnected datasets.
  • Working knowledge of message queuing, stream processing, and highly scalable big data stores.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • Experience with Databricks, Spark, Snowflake, Airflow, and Kafka.
  • Experience with Azure or AWS cloud services.
  • Experience with object-oriented or object-function scripting languages such as Scala, Python, Java, or C++.
  • Strong written and verbal communication skills, including the ability to communicate with technical and business audiences.
  • Demonstrated consulting and client-facing experience, including building relationships, facilitating discussions, and collaborating with client teams.
  • Travel averaging 30–50%, varying with client and project needs.

Responsibilities

  • Support solution architects, software developers, data analysts, and data scientists on data and analytics initiatives.
  • Serve in a lead capacity on client initiatives, collaborating with client stakeholders and technical teams to define and deliver data solutions.
  • Design, develop, and optimize scalable data pipelines and architectures that support client business requirements.
  • Develop and maintain data models and schemas for analytics and reporting, including designing star and snowflake schemas and applying appropriate data modeling techniques.
  • Translate business requirements into technical data solutions and communicate technical concepts to technical and non-technical client stakeholders.
  • Ensure optimal data delivery architecture remains consistent throughout ongoing projects.
  • Support the data needs of multiple teams, systems, and products in a self-directed manner.
  • Identify opportunities to improve data processes, scalability, performance, reliability, and automation.
  • Lead, grow, and mentor a data engineering team in developing, maintaining, and monitoring client data solutions.
  • Assist in defining client solutions, estimating work, supporting proposals, and managing solution delivery.
  • Contribute to project planning, status communication, and other consulting activities throughout the engagement lifecycle.

Desired Qualifications

  • Experience supporting clients in life sciences, consumer products, or retail.
  • Experience in life sciences, consumer products, or retail.
  • A graduate degree in Computer Science, Statistics, Informatics, Information Systems, or an equivalent field.

About the Company

Clarkston Consulting

Consumer products and life sciences consulting

Clarkston Consulting provides specialized consulting services for consumer products and life sciences companies. It delivers tailored solutions in areas like supply chain management, data analytics, and people change management to meet each client’s specific needs. The firm differentiates itself with high client satisfaction (95%), long-term relationships, a global footprint across 16 countries, and a highly qualified workforce where 66% hold advanced degrees or certifications; about 70% of business comes from repeat clients or referrals. Its goal is to help clients improve operations and capabilities over time, delivering sustained value and mutual growth for both clients and the firm.

Company size
201-500
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$15M
Headquarters
Durham, NC
Founded
1991

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