Data Engineering Senior Consultant

Clarkston Consulting is hiring a Data Engineering Senior Consultant to deliver data engineering and analytics solutions for clients in life sciences, consumer products, and retail. The role leads client initiatives, designs and optimizes data pipelines and architectures, develops data models, and mentors data engineering teams.

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 to support analytics and reporting needs, including designing star and snowflake schemas and applying appropriate data modeling techniques
• Translate business requirements into technical data solutions and communicate technical concepts clearly to both technical and non-technical client stakeholders
• Ensure optimal data delivery architecture is consistent throughout ongoing projects
• Be self-directed and comfortable supporting the data needs of multiple teams, systems, and products
• Identify opportunities to improve data processes, scalability, performance, reliability, and automation
• Lead, grow, and mentor a data engineering team in developing, maintaining, and monitoring data solutions for clients
• 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

Requirements:

• Assembling large, complex data sets that meet functional and non-functional business requirements
• Designing and implementing scalable data architectures, pipelines, and data solutions
• Applying data modeling concepts to create effective schemas, including star and snowflake schemas, based on business and analytical requirements
• Working with stakeholders to understand business needs and translate those needs into data and technical solutions
• Communicating recommendations, findings, and technical concepts effectively with client stakeholders and project teams
• Identifying and implementing internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability
• Leveraging the appropriate infrastructure for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies
• Building analytics tools and data solutions that provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Working with cross-functional stakeholders, including Product, Data, Design, and business teams, to address data-related technical issues and support data infrastructure needs
• Working in a consulting environment where collaboration, problem-solving, adaptability, and strong client service are important to successful outcomes
• Working directly with clients in a client-facing role, including leading discussions, facilitating requirements sessions, presenting recommendations, and building trusted working relationships
• Applying consulting skills such as structured problem-solving, requirements gathering, communication, project collaboration, and managing multiple priorities
• 3+ years of experience in a Data Engineer or related data-focused role
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as 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 specific business questions and identify opportunities for improvement
• Strong analytical skills related to working with structured and unstructured datasets
• Experience building processes supporting 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 data stores
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience with big data tools including Databricks, Spark, Snowflake, Airflow, and Kafka
• Experience with Azure or AWS cloud services
• Experience with object-oriented/object function scripting languages such as Scala, Python, Java, and/or C++
• Strong written and verbal communication skills, with the ability to communicate effectively with both technical and business audiences
• Demonstrated consulting and client-facing experience, including the ability to build relationships, facilitate discussions, and work collaboratively with client teams
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or an equivalent field
• Supporting clients in life sciences, consumer products, and retail; experience in one or more of these core industries is preferred
• Experience in life sciences, consumer products, and/or retail is preferred