Johnson Health Tech Companies
Data Engineer
Johnson Health Tech Companies, Cottage Grove, Wisconsin, United States, 53527
Job Type
Full-time
Description
Position Overview:
The Senior Data Engineer will be responsible for designing, developing, and maintaining our data infrastructure, with a focus on transforming and optimizing data across the entire Customer Journey. The ideal candidate will have 7+ years of experience in a large global company environment, expert SQL skills, fluency in Python, and extensive experience optimizing large datasets in Databricks or Snowflake. Experience in modeling data for business intelligence tools like PowerBI, and for machine learning models is essential. This leadership role requires strong data interpretation skills, and an expert ability to communicate technical details to a blended business and technical audience.
Responsibilities:
Data Transformation and Integration:
• Design and implement scalable data pipelines and ETL processes to transform raw data into meaningful data views for our analysts in Sales, Customer Experience, and Supply Chain.
• Integrate various 3rd party data sources, ensuring data quality and consistency across the organization.
Business Intelligence & Analytics Engineering:
• Collaborate with business intelligence teams to support data architecture and provide seamless integration with tools like PowerBI.
• Develop and maintain data models that support BI dashboards and reports, ensuring data accuracy and relevance.
• Ensure data accuracy and reliability by working with Data Stewards and designing processes to maximize data quality
Machine Learning Model Development:
• Work with data scientists to build and deploy machine learning models that enhance business processes, supply chain efficiency, and customer analytics.
• Ensure the integration of machine learning models into existing data pipelines and infrastructure.
Technical Leadership:
• Provide technical guidance and mentorship to more junior team members
• Stay current with industry trends and best practices, incorporating new technologies and methodologies as appropriate.
Collaboration and Communication:
• Work closely with cross-functional teams, including sales, marketing, and customer service, to understand data needs and deliver tailored solutions.
• Communicate complex technical concepts to nontechnical stakeholders in a clear and concise manner.
Job Summary:
The Senior Data Engineer will be responsible for designing, developing, and maintaining our data infrastructure, with a focus on transforming and optimizing data across the entire Customer Journey. The ideal candidate will have 5-7 years of experience in data engineering &/or data science, extensive knowledge of Databricks or Snowflake, and expert SQL skills. Additionally, experience in supporting data architecture for business intelligence tools like PowerBI, and for machine learning models is essential. This role requires strong data interpretation skills, and the ability to communicate technical details within a business context.
Key Responsibilities:
Data Transformation and Integration:
• Design and implement scalable data pipelines and ETL processes to transform raw data into meaningful insights for supply chain, customer, and marketing analytics.
• Integrate various data sources, ensuring data quality and consistency across the organization.
Business Intelligence & Analytics Engineering:
• Collaborate with business intelligence teams to support data architecture and provide seamless integration with tools like PowerBI.
• Develop and maintain data models that support BI dashboards and reports, ensuring data accuracy and relevance.
• Create impactful data visualizations to communicate key trends and insights
Machine Learning Model Development:
• Work with data scientists to build and deploy machine learning models that enhance business processes, supply chain efficiency, and customer analytics.
• Ensure the integration of machine learning models into existing data pipelines and infrastructure.
Technical Leadership:
• Provide technical guidance and mentorship
• Stay current with industry trends and best practices, incorporating new technologies and methodologies as appropriate.
Collaboration and Communication:
• Work closely with cross-functional teams, including supply chain, marketing, and customer service, to understand data needs and deliver tailored solutions.
Requirements
• Bachelor's or Master's degree in computer science, Information Technology, Economics or a related quantitative field.
• 7+ years of experience in data engineering for a large, global organization, with a strong emphasis on transforming and optimizing data for Sales, Customer and Supply-Chain Analytics in both a DTC and B2B context.
• Expert level SQL skills, with the ability to write complex queries and optimize them for performance.
• Experience in supporting data architecture for business intelligence tools, particularly PowerBI.
• Experience leading code reviews, designing and implementing QA of data pipelines
• Fluency in programming languages such as Python or Scala.
• Prior experience in AWS Databricks or Snowflake
• Strong understanding of data warehousing concepts, ETL processes, and data modeling.
• Proven experience in building and deploying machine learning models.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.
Preferred Qualifications:
• Experience with BI tools such as PowerBI, Looker or Tableau.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud.
• Experience with Marketing Operations tools like Braze
• Advanced degree in a quantitative field
Full-time
Description
Position Overview:
The Senior Data Engineer will be responsible for designing, developing, and maintaining our data infrastructure, with a focus on transforming and optimizing data across the entire Customer Journey. The ideal candidate will have 7+ years of experience in a large global company environment, expert SQL skills, fluency in Python, and extensive experience optimizing large datasets in Databricks or Snowflake. Experience in modeling data for business intelligence tools like PowerBI, and for machine learning models is essential. This leadership role requires strong data interpretation skills, and an expert ability to communicate technical details to a blended business and technical audience.
Responsibilities:
Data Transformation and Integration:
• Design and implement scalable data pipelines and ETL processes to transform raw data into meaningful data views for our analysts in Sales, Customer Experience, and Supply Chain.
• Integrate various 3rd party data sources, ensuring data quality and consistency across the organization.
Business Intelligence & Analytics Engineering:
• Collaborate with business intelligence teams to support data architecture and provide seamless integration with tools like PowerBI.
• Develop and maintain data models that support BI dashboards and reports, ensuring data accuracy and relevance.
• Ensure data accuracy and reliability by working with Data Stewards and designing processes to maximize data quality
Machine Learning Model Development:
• Work with data scientists to build and deploy machine learning models that enhance business processes, supply chain efficiency, and customer analytics.
• Ensure the integration of machine learning models into existing data pipelines and infrastructure.
Technical Leadership:
• Provide technical guidance and mentorship to more junior team members
• Stay current with industry trends and best practices, incorporating new technologies and methodologies as appropriate.
Collaboration and Communication:
• Work closely with cross-functional teams, including sales, marketing, and customer service, to understand data needs and deliver tailored solutions.
• Communicate complex technical concepts to nontechnical stakeholders in a clear and concise manner.
Job Summary:
The Senior Data Engineer will be responsible for designing, developing, and maintaining our data infrastructure, with a focus on transforming and optimizing data across the entire Customer Journey. The ideal candidate will have 5-7 years of experience in data engineering &/or data science, extensive knowledge of Databricks or Snowflake, and expert SQL skills. Additionally, experience in supporting data architecture for business intelligence tools like PowerBI, and for machine learning models is essential. This role requires strong data interpretation skills, and the ability to communicate technical details within a business context.
Key Responsibilities:
Data Transformation and Integration:
• Design and implement scalable data pipelines and ETL processes to transform raw data into meaningful insights for supply chain, customer, and marketing analytics.
• Integrate various data sources, ensuring data quality and consistency across the organization.
Business Intelligence & Analytics Engineering:
• Collaborate with business intelligence teams to support data architecture and provide seamless integration with tools like PowerBI.
• Develop and maintain data models that support BI dashboards and reports, ensuring data accuracy and relevance.
• Create impactful data visualizations to communicate key trends and insights
Machine Learning Model Development:
• Work with data scientists to build and deploy machine learning models that enhance business processes, supply chain efficiency, and customer analytics.
• Ensure the integration of machine learning models into existing data pipelines and infrastructure.
Technical Leadership:
• Provide technical guidance and mentorship
• Stay current with industry trends and best practices, incorporating new technologies and methodologies as appropriate.
Collaboration and Communication:
• Work closely with cross-functional teams, including supply chain, marketing, and customer service, to understand data needs and deliver tailored solutions.
Requirements
• Bachelor's or Master's degree in computer science, Information Technology, Economics or a related quantitative field.
• 7+ years of experience in data engineering for a large, global organization, with a strong emphasis on transforming and optimizing data for Sales, Customer and Supply-Chain Analytics in both a DTC and B2B context.
• Expert level SQL skills, with the ability to write complex queries and optimize them for performance.
• Experience in supporting data architecture for business intelligence tools, particularly PowerBI.
• Experience leading code reviews, designing and implementing QA of data pipelines
• Fluency in programming languages such as Python or Scala.
• Prior experience in AWS Databricks or Snowflake
• Strong understanding of data warehousing concepts, ETL processes, and data modeling.
• Proven experience in building and deploying machine learning models.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.
Preferred Qualifications:
• Experience with BI tools such as PowerBI, Looker or Tableau.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud.
• Experience with Marketing Operations tools like Braze
• Advanced degree in a quantitative field