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Sr. Data Engineer

Draper, UT (Hybrid)

Who we are

SeekWell is the parent company of 1-800 Contacts, Luna, and Hello Eyes. Our goal is to make it simpler, easier, and more accessible for people to get the vision care they need. We maintain the legendary, award-winning culture 1-800 Contacts started almost 30 years ago and continue to develop innovative, pioneering products and businesses that make consumers cheer and optometrists squirm. We’re owned by KKR – one of the world’s largest and most successful private equity investment companies. We’ve built an excellent company and changed an industry by putting the customer first, always. The best is yet to come!

Why you want this job

As a Data Engineer III, you will be a senior member of the team, tasked with scaling and optimizing our data systems while mentoring junior and mid-level engineers. Reporting to Ken Myers, you’ll lead the development of key machine learning projects, including a recommendation engine, and design new data models and ETL jobs to support business processes. You'll optimize media spend pipelines and collaborate across teams, including marketing, to ensure seamless data operations and drive actionable insights. This role is perfect for someone passionate about solving complex problems, building efficient data solutions, and mentoring others.

What you’ll do

  • Lead collaboration with product and engineering teams to develop scalable data solutions addressing operational and business needs.
  • Mentor junior and mid-level engineers, demonstrating best practices, guiding them through challenges, and fostering their growth.
  • Design, build, and maintain data infrastructure for ETL processes, leveraging technologies such as Databricks, SQL Server, and AWS.
  • Develop and optimize analytics tools, enabling actionable insights into metrics such as customer acquisition, operational efficiency, and media spend.
  • Create advanced reporting tools and dashboards using platforms like Tableau, Looker, or Power BI to support data-driven decisions.
  • Implement and improve ETL jobs, supporting machine learning models and other critical business workflows.
  • Work with streaming data systems like Kafka or Pub/Sub to enable real-time data processing and decision-making.
  • Communicate technical concepts effectively to cross-functional stakeholders, aligning efforts with business goals and priorities.

What you'll need

Minimum Qualifications

  • 5+ years of experience in a Data Engineer role or a related field, with a bachelor's degree in Computer Science, Statistics, Information Systems, or another quantitative field.
  • Expert knowledge of SQL and advanced experience in data warehouse design and data modeling, including star schema, facts, and dimensions.
  • Expertise in ETL, data pipeline technologies, Pub/Sub models, REST APIs, and workflow management tools.
  • Proficiency with data warehousing platforms such as Databricks or Snowflake and relational database systems like SQL Server and MySQL.
  • Programming proficiency in Python, with experience leveraging APIs for data integration and building scalable pipelines.
  • Proficiency in cloud services (AWS, Azure, Google Cloud), including designing and managing data infrastructure on cloud platforms.
  • Hands-on experience with stream-processing systems such as Apache Spark and Kafka.
  • Experience with data visualization tools like Tableau, Power BI, or Looker, with the ability to create actionable and optimized dashboards.

Preferred Qualifications

  • Direct experience with Databricks or Snowflake.
  • Advanced experience in building, optimizing, and maintaining ETL processes in cloud environments.
  • Proven track record in designing data warehouses and building ETL jobs to populate warehouse objects.
  • Demonstrated experience in creating advanced reporting tools that provide actionable insights to stakeholders.

Why we will love you

  • You deeply understand data engineering, with expertise in building scalable and efficient infrastructures.
  • You thrive in optimizing cloud platforms, data pipelines, and analytics tools to support business goals.
  • You take initiative and communicate clearly, quickly getting up to speed and taking ownership of processes.
  • You’re passionate about mentoring others and enjoy guiding a team to success.
  • You’re a problem-solver, always seeking opportunities to improve systems and deliver impact.
  • You excel in fast-paced environments, confidently tackling complex challenges.

Perks

  • Free eye exams for your entire family
  • Deep discounts on lenses, glasses, and other services
  • Amazing healthcare coverage
  • 401(k) match
  • Flexible PTO
  • Tuition reimbursement program
  • In-house restaurant with highly discounted meals (Steak dinner under $6)
  • Free snacks, ice cream, and drinks every day
  • Full onsite gym

 

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

 #LI-Hybrid

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Expert:
You have extensive experience designing star schemas and implementing dimensional models for large-scale data projects. You understand complex business requirements and translate them into optimized, scalable data models. You mentor others on best practices and have led successful implementations in multiple projects.

Advanced:
You have significant experience designing and implementing star schemas and dimensional models. You can optimize models for analytical performance, address common challenges, and support reporting needs independently.

Intermediate:
You have hands-on experience with star schema design and dimensional modeling. You understand the core concepts, such as fact and dimension tables, and can apply them in small to mid-sized projects with some guidance.

Beginner:
You have a basic understanding of star schema design and dimensional modeling concepts, such as fact tables, dimension tables, and their relationships, but lack real-world implementation experience.

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Expert:
You are highly proficient in SQL and data warehousing concepts. You have designed and implemented complex data models and optimized large-scale relational databases for performance and scalability. You regularly perform advanced query tuning and have extensive experience in database partitioning, indexing strategies, and normalization/denormalization practices. You mentor others in best practices for database design and optimization.

Advanced:
You have extensive experience with SQL, and you are skilled in creating and optimizing relational databases. You have worked with data models, ensuring data integrity, and have a solid understanding of database indexing, partitioning, and optimization techniques. You regularly troubleshoot and optimize SQL queries and participate in designing efficient database structures.

Intermediate:
You have practical experience with SQL, writing queries, and managing relational databases. You are familiar with data modeling principles and can create and optimize database schemas with guidance. You handle day-to-day operations, such as querying and managing databases, but may need help with complex optimization or architecture design.

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You have basic knowledge of SQL and relational databases. You understand core concepts like tables, joins, and basic query writing. You may have created simple data models and performed basic database management tasks, but you are still learning about advanced database design, query optimization, and indexing.

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Expert:
You are highly proficient in Python, Java, or Scala, with extensive experience building and optimizing data pipelines. You write efficient, production-level code and have deep knowledge of libraries and frameworks for data processing and transformation. You regularly optimize code for performance and scalability, and mentor others in coding best practices.

Advanced:
You have extensive hands-on experience in Python, Java, or Scala, and are comfortable building, optimizing, and troubleshooting data pipelines. You write clean, efficient code and have experience using these languages for tasks like ETL, data transformation, and workflow automation.

Intermediate:
You have practical experience with Python, Java, or Scala and have built data pipelines using these languages. You are comfortable writing scripts for data transformation and integration tasks but may need assistance with more complex or large-scale optimizations.

Beginner:
You have basic proficiency in Python, Java, or Scala. You understand core programming concepts and have written basic scripts or programs but are still learning to apply these languages effectively for building and optimizing data pipelines.

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Expert:
You are highly proficient in creating complex dashboards and reports using Tableau, PowerBI, or Looker. You have optimized reports for performance and business insights, built advanced calculations, and integrated various data sources. You mentor others in data visualization best practices.

Advanced:
You have extensive experience using Tableau, PowerBI, or Looker to create dashboards and reports. You are skilled at optimizing performance, working with multiple data sources, and building reports that drive business decisions.

Intermediate:
You have practical experience creating dashboards and reports with Tableau, PowerBI, or Looker. You can handle most day-to-day tasks but may need guidance with more complex visualizations or performance optimizations.

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You have basic knowledge of data visualization tools like Tableau, PowerBI, or Looker. You can create simple reports and dashboards but are still learning how to use these tools to their full potential.

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Expert:
You are highly proficient in stream-processing systems, with extensive experience using Apache Spark and Kafka for large-scale data processing. You have designed and managed Spark jobs and Kafka streams in production, optimized for performance, and ensured fault tolerance. You mentor others in stream-processing best practices and troubleshooting.

Advanced:
You have hands-on experience with stream-processing systems like Apache Spark and Kafka in production environments. You are comfortable configuring and managing streams, tuning for performance, and troubleshooting issues. You have used Spark for distributed data processing and Kafka for real-time data streaming.

Intermediate:
You have practical experience working with stream-processing systems, including building and managing Spark jobs or Kafka streams. You are proficient in day-to-day tasks but may require guidance with more advanced configurations, scaling, or troubleshooting.

Beginner:
You have basic knowledge of stream-processing systems like Apache Spark and Kafka. You understand core concepts and may have worked on simple tasks, but you are still learning how to apply these systems to larger-scale data processing.

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Expert:
You have designed, implemented, and managed complex data infrastructure on cloud platforms (AWS, Azure, or Google Cloud). You are well-versed in cloud-native services such as S3, EC2, RDS, and cloud-based data warehouses like Redshift, BigQuery, or Azure Synapse. You handle security, scalability, and optimization of cloud resources, managing cost and performance efficiently. You have experience with hybrid cloud/on-premises setups and disaster recovery strategies.

Advanced:
You have significant hands-on experience with cloud platforms and have managed data infrastructure on AWS, Azure, or Google Cloud. You are comfortable with services like S3, IAM, and cloud databases, and can architect solutions to ensure performance and scalability. You have implemented security protocols and optimized resource usage within cloud environments.

Intermediate:
You have experience working with cloud services and have set up and managed cloud-based data infrastructure under supervision. You understand basic concepts like storage, compute, and networking within cloud environments and have some experience configuring services like S3, EC2, or similar. However, you may require assistance with more advanced or complex cloud infrastructure tasks.

Beginner:
You have basic knowledge of cloud platforms (AWS, Azure, or Google Cloud) and have worked on setting up basic services. You understand the core components like storage, computing, and networking but are still learning to manage more complex cloud infrastructure or data pipelines on the cloud.

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Expert:
You are highly proficient in designing, implementing, and managing end-to-end data pipelines using technologies like Apache Kafka, Pub/Sub, and workflow management tools (e.g., Airflow). You have led the design and deployment of complex data workflows in production environments, ensuring high availability, fault tolerance, and data integrity. You mentor others on optimizing data flows and resolving pipeline-related issues.

Advanced:
You have significant experience managing and optimizing data pipelines using Kafka, Pub/Sub models, and tools like Airflow. You are capable of designing efficient data pipelines, handling high-volume data streams, and ensuring that the systems run smoothly and securely. You troubleshoot and optimize pipeline performance with little supervision.

Intermediate:
You have practical experience with data pipeline technologies and have built and managed data pipelines for various tasks. You understand basic principles of Pub/Sub models and have used workflow management tools like Airflow to orchestrate data workflows. However, you may need guidance with more complex implementations or troubleshooting.

Beginner:
You have some knowledge of data pipeline technologies and Pub/Sub models, and you may have been involved in building simple data pipelines. You understand core concepts but are still learning how to design and manage more complex workflows and handle larger data streams.

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