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Data Strategy Engineer Jobs in Utah (NOW HIRING)

Senior Data Engineer

Lehi, UT ยท On-site

$99K - $135K/yr

As a Senior Data Engineer, you will be a high-impact "Game Changer" responsible for architecting ... strategies. This is your chance to lead high-stakes technical initiatives that directly accelerate ...

Senior Data Engineer

Lehi, UT

$99K - $135K/yr

As a Senior Data Engineer, you will be a high-impact "Game Changer" responsible for architecting ... strategies. This is your chance to lead high-stakes technical initiatives that directly accelerate ...

Senior Data Engineer

Lehi, UT

$99K - $135K/yr

As a Senior Data Engineer, you will be a high-impact "Game Changer" responsible for architecting ... strategies. This is your chance to lead high-stakes technical initiatives that directly accelerate ...

Senior Data Engineer

Midvale, UT ยท On-site

$100K - $135K/yr

Support backup, recovery, and resiliency strategies across data warehouse and staging environments ... Partner with data analysts, engineers, DevOps, and business stakeholders to deliver trusted data ...

Develop and implement audience segmentation strategies using advanced SQL queries and data ... Collaborate with cross-functional teams such as IT and engineering to integrate data from various ...

Develop and implement audience segmentation strategies using advanced SQL queries and data ... Collaborate with cross-functional teams such as IT and engineering to integrate data from various ...

Develop and implement audience segmentation strategies using advanced SQL queries and data ... Collaborate with cross-functional teams such as IT and engineering to integrate data from various ...

Develop and implement audience segmentation strategies using advanced SQL queries and data ... Collaborate with cross-functional teams such as IT and engineering to integrate data from various ...

Technical Senior Product Manager

Salt Lake City, UT ยท On-site

$122K - $161K/yr

KEY RESPONSIBILTIES Data Strategy * Define and execute strategy for data management across a large ... Partner with engineering and architecture teams to deliver initiatives on time and within budget ...

Share product feedback with Engineering and Product teams, including market patterns, feature gaps ... Basic understanding of APIs, webhooks, or data integrations. * Familiarity with SQL, Python, or ...

AI Strategy Consultant

Provo, UT ยท On-site

$50K - $90K/yr

Share product feedback with Engineering and Product teams, including market patterns, feature gaps ... Basic understanding of APIs, webhooks, or data integrations. * Familiarity with SQL, Python, or ...

Technical Senior Product Manager

Salt Lake City, UT ยท Hybrid

$122K - $161K/yr

KEY RESPONSIBILTIES Data Strategy * Define and execute strategy for data management across a large ... Partner with engineering and architecture teams to deliver initiatives on time and within budget ...

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Data Strategy Engineer information

What is the difference between Data Strategy Engineer vs Data Analyst?

AspectData Strategy EngineerData Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; certifications in data management or cloud platformsBachelor's in Statistics, Mathematics, or related fields; certifications in data analysis tools
Work EnvironmentCollaborates with data engineers, business strategists, and IT teams to develop data strategiesWorks with data sets to generate reports, dashboards, and insights for business decisions
Employer & Industry UsageUsed in tech, finance, and consulting firms focusing on data-driven strategiesCommon across various industries for operational and marketing insights

The Data Strategy Engineer focuses on designing and implementing data strategies to support business goals, often working on data architecture and governance. In contrast, the Data Analyst primarily interprets data to generate reports and insights. Both roles require strong analytical skills, but the Data Strategy Engineer has a broader scope involving strategic planning and data infrastructure.

What jobs will boom in 10 years?

Data Strategy Engineers and related data roles are expected to grow significantly as organizations increasingly rely on data-driven decision-making, advanced analytics, and AI integration. Skills in data management, cloud platforms, and programming languages like Python or SQL will be highly valuable in this evolving job market.

Is 40 too late for data science?

For a Data Strategy Engineer or similar data-focused roles, starting a career in data science at age 40 is feasible, as many professionals transition into data roles later in life. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or SQL, along with practical experience. Age is less important than skills, continuous learning, and adapting to industry demands.

How much does a data strategist make?

A data strategist's salary typically ranges from $80,000 to $150,000 annually, depending on experience, industry, and location. Senior roles or those requiring advanced skills in data analysis, machine learning, or strategic planning may offer higher compensation.

Can I make 200K as a Data Engineer?

Data Strategy Engineers and Data Engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, data architecture, and certifications. Salaries vary by industry, location, and company size, with senior roles and specialized expertise commanding higher compensation.
What are popular job titles related to Data Strategy Engineer jobs in Utah? For Data Strategy Engineer jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Data Strategy Engineer jobs? Cities in Utah with the most Data Strategy Engineer job openings:
Senior Data Engineer

Senior Data Engineer

Pattern

Lehi, UT โ€ข On-site

$99K - $135K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Job description

Are you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list.
Pattern accelerates brands on global ecommerce marketplaces leveraging proprietary technology and AI. Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of ecommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting and customer service. Hundreds of global brands depend on Pattern's ecommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces-including Amazon, Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre. To learn more, visit pattern.com or email [email protected].
Pattern has been named one of the fastest growing tech companies headquartered in North America by Deloitte and one of best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek's Global Most Loved Workplacesยฎ.
As a Senior Data Engineer, you will be a high-impact "Game Changer" responsible for architecting and building the very foundation of Pattern's data-driven future. You will tackle massive, petabyte-scale challenges, transforming raw data into high-octane fuel for our AI models and global marketplace strategies. This is your chance to lead high-stakes technical initiatives that directly accelerate growth for hundreds of global brands in a fast-paced, elite engineering environment.
What is a day in the life of a Senior Data Engineer?
  • Designing and implementing robust ETL/ELT pipelines using Airflow, DBT, and cloud-native architectures.
  • Writing sophisticated, production-grade Python code to automate data orchestration and processing.
  • Building/optimizing complex SQL queries and dimensional models for OLAP and OLTP based systems
  • Collaborating with cross-functional teams to ingest and harmonize data from dozens of global marketplaces.
  • Building and maintaining infrastructure-as-code and containerized workflows to ensure platform reliability.
  • Leveraging AI thoughtfully to optimize processes and workflows

What will I need to thrive in this role?
  • Bachelor's degree in Computer Science, Data Science, or a related technical field (or equivalent experience).
  • 7+ years of professional data engineering experience with a heavy focus on ETL/ELT and data modeling.
  • 5+ years of expert-level SQL mastery, including window functions, CTEs, and deep performance tuning.
  • 4+ years of professional Python development specifically tailored for data pipelines and tooling.
  • 3+ years of hands-on experience building/optimizing large-scale data warehouses like Snowflake, BigQuery, or Redshift.
  • Proficiency with open-source frameworks such as Apache Spark, Trino, Kafka, and Debezium.
  • A "Data Fanatic" mindset with experience handling petabyte-scale diverse datasets.

What does high performance look like?
  • Successfully executing the migration or optimization of massive data streams with zero downtime.
  • Consistently delivering clean, well-documented, and high-quality code that sets the standard for the engineering team.
  • Acting as a 'Doer' by taking the initiative to resolve platform bottlenecks before they impact partners.
  • Elevating the technical bar of the team through mentorship and the introduction of innovative engineering practices.

What is my potential for career growth?
  • Opportunity to lead major architectural shifts within a rapidly expanding global tech company.
  • Regular networking and collaboration with high-level technical leadership and AI experts.
  • Upward mobility toward Staff Data Engineer or specialized technical leadership roles.
  • Continuous learning opportunities with cutting-edge technologies like Apache Iceberg and real-time streaming architectures.

What does success look like in the first 30, 60, 90 days?
  • 30 Days: Complete onboarding, gain a deep understanding of current data architectures, and begin contributing to existing projects.
  • 60 Days: Identify and implement at least one major performance optimization within the data environment and lead a small-scale pipeline project.
  • 90 Days: Take responsibility for a significant segment of data processes, collaborating with other engineers and contributing to the long-term roadmap for lakehouse integration.

What is the team like?
  • This role reports directly to the Director of Data Engineering.
  • You will be joining a growing team of data professionals that span multiple geographies.
  • In this role, you will collaborate closely with Data Scientists, Software Engineers, AI Engineers, and Product Managers as well as other departments including Marketing and Sales.

Sounds great! What's the company culture? We are looking for individuals who are:
  • Game Changers- A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches a realistic timeline to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern's processes and outcomes.
  • Data Fanatics- A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of the solutions using data.
  • Partner Obsessed- An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner's expectations, and delivers results that exceed them, prioritizes the needs of your partners, and takes the time to create a personable experience for those interacting with Pattern.
  • Team of Doers- Someone who is a part of a team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners.

What is the hiring process?
  • Phone Interview with Talent Acquisition
  • Video Interview
  • Onsite Interview
  • Executive Review
  • Offer

How can I stand out as an applicant?
  • Strong Nice-to-Haves: Expertise in AWS services (Terraform, EKS, Lambda), experience with Apache Iceberg or Delta Lake, and a background in real-time streaming (Kafka/Kinesis).
  • Interview Tips: Be prepared to discuss your experience managing large-scale data outages or complex optimizations; highlight any 'Partner Obsessed' moments where your data work solved a critical business problem; and demonstrate your 'Data Fanatic' nature through a deep dive into a past side project or complex pipeline you built.

Why should I work at Pattern?
Pattern offers big opportunities to make a difference in the ecommerce industry! We are a company full of talented people that evolves quickly and often. We set big goals, work tirelessly to achieve them, and we love our Pattern community. We also believe in having fun and balancing our lives, so we offer awesome benefits that include:
- Unlimited PTO
- Paid Holidays
- Onsite Fitness Center
- Company Paid Life Insurance
- Casual Dress Code
- Competitive Pay
- Health, Vision, and Dental Insurance
- 401(k) match. Pattern matches 100% of the first 3% in eligible compensation deferred and 50% of the next 2% in eligible compensation deferred.
Pattern provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability, status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.