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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Pattern Inc. - **Location:** Lehi, UT, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Query Performance, Artificial Intelligence, Airflow, Amazon S3, Data Analysis, Big Data, BigQuery, Cloud Computing, Profiling, Information Systems, Databases, Data Architecture, Data Auditing, Information Engineering, Data Governance, Data Infrastructure, Data Mining, Data Visualization, Data Warehousing, Relational Databases, Query Languages, Amazon DynamoDB, Elasticsearch, Information Management, Machine Learning, Systems Development Life Cycle, Requirements Management, SQL Stored Procedures, SQL Databases, Data Streaming, Tableau (Software), Data Processing, Apache Cassandra, Time Series Databases, Snowflake, Apache Spark, AWS Lambda, Data Lakes, Information Technology, Cassandra, Data Analytics, Star Schema, Non-relational Database, Data Management, Amazon Simple Queue Service (SQS), Database Rules and Triggers, Data Pipelines, Amazon Redshift - **Published:** August 6, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-lehi-ut--b0e063be-1616-4220-b602-18a15484912d ## About the Role We are seeking a scrappy and motivated Data Engineer to join our growing team. In this role, you will collaborate with cross-functional teams to design, build, and maintain scalable data pipelines, manage and optimize data flows, and support data-driven decision-making processes. This position is ideal for individuals with some hands-on experience in data engineering who are eager to grow and develop their technical expertise. This is a full-time role and will work a hybrid schedule in Lehi, Utah., * Bachelor's Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, related field, or equivalent professional experience. * 3-5 years of experience working with SQL. * Familiarity with implementing modern data architecture-based data warehouses. * Familiarity with data warehouses such as Redshift, BigQuery, or Snowflake and understanding of data architecture design. * Strong communication skills (both in presentation and comprehension). * Exposure to data visualization tools like Tableau or ThoughtSpot. Preferred Qualifications * Experience working with time series databases. * Experience with SQL, including the ability to write stored procedures, triggers, analytic/windowing functions, and tuning. * Knowledge of Snowflake. * Familiarity with Big Data, non-relational databases, Machine Learning and Data Mining. * Familiarity with cloud-based technologies including SNS, SQS, SES, S3, Lambda, and Glue. * Familiarity with modern data platforms like Redshift, Cassandra, DynamoDB, Apache Airflow, Spark, or ElasticSearch. * Understanding of Data Quality and Data Governance., AWS Lambda, Advertising, Amazon Simple Storage Service (S3), Analysis Skills, Apache Cassandra, Apache Spark, Architectural Design, Artificial Intelligence (AI), Auditing, Big Data, Business Model, Business Operations, Cloud Computing, Communication Skills, Computer Science, Content Management, Cross-Functional, Customer Support/Service, Data Analysis, Data Lake, Data Management, Data Mining, Data Processing, Data Quality, Data Science, Data Visualization Tools, Data Warehousing, Database Programming Languages, Database Triggers, Dental Insurance, Elasticsearch, Establish Priorities, Fitness, Forecasting, Global Branding, Identify Issues, Information Technology & Information Systems, Intellectual Property (IP), Life Insurance, Logistics, Machine Learning, Presentation/Verbal Skills, Pricing, Problem Solving Skills, Procedure Development, Relational Databases (RDBMS), Requirements Management, Revenue Growth, SQL (Structured Query Language), Sales Pipeline, Scalable System Development, Simple Queue Service (SQS), Snowflake Schema, Stored Procedures, Tableau, Technical/Engineering Design, Vision Plan, Writing Skills, eCommerce ## Description * Develop, deploy, and support real-time, automated, scalable data streams from a variety of sources into the data lake or data warehouse. * Develop and implement data auditing strategies and processes to ensure data quality; identify and resolve problems associated with large-scale data processing workflows; implement technical solutions to maintain data pipeline processes and troubleshoot failures. * Collaborate with technology teams and partners to specify data requirements and provide access to data. * Tune application and query performance using profiling tools and SQL or other relevant query languages. * Understand business, operations, and analytics requirements for data * Build data expertise and own data quality for assigned areas of ownership. * Work with data infrastructure to triage issues and drive to resolution. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Making Data Warehouses fast. 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