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Data Engineer 300K Jobs (NOW HIRING)

Prodege LLC

Principal Data Engineer

... 300K queries per day across multiple engines. This is a deeply hands-on principal role. We are ... The evolution of Data Engineering toward a more AI-first way of working What Makes This Role ...

Transparent Search Group

AI Engineer

Sunnyvale, CA · Hybrid

$225K - $300K/yr

AI Engineer Automotive Software Innovation (Sunnyvale, CA | Hybrid | $225K to $300K) About the ... Collaborate with data and engineering teams to operationalize ML pipelines using MLOps best ...

Mackenzie Health Care

Big Data Architect

New York, NY · On-site

$69.75 - $89.75/hr

... Programming paradigm, HBase, Pig, Hive Cassandra 2+ years experience with administration ... 300k + DOE - Excellent benefits * If interested, please follow the link that is provided - Elaine ...

MLabs

Senior Infrastructure Engineer

$180K - $300K/yr

Remote - United States Compensation: $180K - $300K Join a stellar team of leaders and experts in ... Your data may be shared only with clients and trusted partners where necessary for recruitment ...

Mackenzie Health Care

Big Data Architect

New York, NY · On-site

$69.75 - $89.75/hr

... Programming paradigm, HBase, Pig, Hive Cassandra 2+ years experience with administration ... 300k + DOE - Excellent benefits * If interested, please follow the link that is provided - Elaine ...

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Data Engineer 300K information

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$44.5K

$129.7K

$177.5K

How much do data engineer 300k jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data engineer 300k in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are Data Engineers and what do they do?

Data Engineers are professionals who design, build, and maintain the systems and infrastructure needed to collect, store, and process large sets of data. Their work enables organizations to manage data efficiently and make it accessible for analysis by data scientists and other stakeholders. Data Engineers often work with big data technologies, databases, and tools for data integration, ensuring high performance, reliability, and scalability of data pipelines. Earning a high salary, such as $300K, typically requires advanced expertise, experience with complex architectures, and contributions to large-scale or mission-critical projects.

What are some common challenges Data Engineers face when managing large-scale data pipelines, and how can they be addressed?

Data Engineers often encounter challenges such as ensuring data quality, optimizing pipeline performance, and handling data schema changes across large-scale, distributed systems. Addressing these issues typically involves implementing robust data validation checks, utilizing scalable data processing frameworks like Apache Spark, and adopting version control practices for data schemas. Collaboration with data scientists, analysts, and DevOps teams is also key to addressing integration and deployment challenges, ensuring that data pipelines remain reliable and efficient as business needs evolve.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need strong programming skills (especially in Python, Java, or Scala), expertise in database management, and a solid understanding of data architecture, typically supported by a degree in computer science or a related field. Familiarity with tools like SQL, Apache Spark, Hadoop, and cloud platforms such as AWS or Azure, as well as certifications like AWS Certified Data Analytics, are commonly required. Excellent problem-solving abilities, collaboration, and effective communication distinguish top performers in this role. These skills are vital for efficiently designing, building, and maintaining scalable data infrastructure that enables organizations to make data-driven decisions.

What is the difference between Data Engineer 300K vs Data Scientist?

AspectData Engineer 300KData Scientist
Required SkillsSQL, Python, ETL, Big Data toolsStatistics, Machine Learning, Python/R
Work EnvironmentData pipelines, infrastructure, backend systemsData analysis, modeling, research
Industry UsageData engineering teams, cloud platformsAnalytics teams, research departments

Data Engineer 300K and Data Scientist roles often share skills like Python and data handling. However, Data Engineer 300K focuses on building and maintaining data infrastructure, while Data Scientists analyze data to generate insights. Both roles are vital in data-driven organizations, but their daily tasks and skill emphasis differ significantly.

More about Data Engineer 300K jobs
What cities are hiring for Data Engineer 300K jobs? Cities with the most Data Engineer 300K job openings:
What states have the most Data Engineer 300K jobs? States with the most job openings for Data Engineer 300K jobs include:
What job categories do people searching Data Engineer 300K jobs look for? The top searched job categories for Data Engineer 300K jobs are:
Data Engineer 300K jobs near you
Infographic showing various Data Engineer 300K job openings in the United States as of July 2026, with employment types broken down into 32% Internship, 27% Full Time, 2% Part Time, 2% Contract, 36% Nights, and 1% Summer. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Principal Data Engineer

Principal Data Engineer

Prodege LLC

Remote

Full-time

Medical, Dental, Vision, Life, PTO

Posted yesterday

Job description

Job Description:
Prodege:
A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.
As an organization, we go the extra mile to "Create Rewarding Moments" every day for our partners, consumers, and team. Come join us today!
Strategic Imperative:
We are looking for a Principal Data Engineer to shape the future of data at Prodege.This is a high-impact role for someone who wants to own more than pipelines. You will help build the next-generation data platform that powers analytics, experimentation, machine learning, business intelligence, and revenue-driving decision-making across Prodege's products and business domains.
In this role, you will own the data stack end to end - from platform architecture and data modeling, to pipeline delivery, governance, observability, and the business outcomes those systems enable. You will work across a complex ecosystem spanning owned and operated brands, performance marketing, rewards, customer experience, and machine learning, helping the company scale faster on a more trusted, modern, and AI-ready data foundation.
You will help build the next-generation data platform supporting a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, operating at real engineering scale with 400TB total data footprint, 100TB Iceberg lake and growing, 50M raw events per day, 500M records of daily pipeline throughput, 50 Kafka topics and growing, and 300K queries per day across multiple engines.
This is a deeply hands-on principal role. We are looking for someone who leads by building, shipping, and modernizing production data systems - not someone who stays only at the architecture or strategy layer. If you enjoy solving hard data problems, building durable platforms, and helping teams move faster with better foundations, this role is for you.
What You'll Own
  • The architecture and evolution of the next-generation data platform / lakehouse
  • High-scale batch, ELT, and near-real-time data pipelines that power BI, experimentation, ML, and product systems
  • Trusted data foundations across Snowflake, dbt, Iceberg, Trino, streaming, event-driven systems, and similar modern data technologies
  • Platform patterns for Medallion architecture, data contracts, schema evolution, governance, and observability
  • Data foundations that support machine learning, feature pipelines, experimentation, and decisioning
  • Hands-on technical leadership across the Data Engineering organization through direct contribution, design reviews, and mentoring
  • The evolution of Data Engineering toward a more AI-first way of working
What Makes This Role Exciting
  • You will build the foundation that powers analytics, BI, experimentation, and machine learning across the company
  • You will own data from architecture through production outcome, not just pipeline delivery
  • You will work across a complex ecosystem spanning owned brands, rewards, performance marketing, customer experience, and ML
  • You will help power a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards
  • You will work on a real production platform at scale: 400TB data footprint, 100TB Iceberg lake, 50M daily events, 500M daily pipeline records, 50 Kafka topics and growing, and 300K daily queries
  • You will have principal-level scope to influence platform design, standards, and the future of data engineering across the company
  • You will help push the data organization toward a more AI-first engineering future
What You'll Do
  • Lead the design, build, and evolution of the next-generation data platform across Snowflake, dbt, Iceberg, Trino, Kafka, and related technologies
  • Personally drive critical implementations in the data platform, modernizing legacy pipelines and proving out new approaches before scaling them across the team
  • Build and optimize high-scale batch, ELT, and near-real-time pipelines for BI, product, experimentation, and ML use cases
  • Establish durable platform patterns around Medallion architecture, data contracts, schema management, lineage, observability, and governance
  • Design and evolve scalable data models and data marts that support business reporting, self-service analytics, and ML workloads
  • Make key decisions on tooling, orchestration, storage patterns, performance, reliability, and cost efficiency
  • Partner closely with ML, BI, Product, Engineering, Analytics, and business stakeholders to turn business needs into scalable technical designs
  • Build data foundations that support model training, feature pipelines, experimentation, and AI-driven applications
  • Drive an AI-first mindset by using AI to accelerate development, debugging, design exploration, testing, and documentation
  • Mentor data engineers and raise the bar on technical quality, maintainability, and engineering discipline
Must Have
  • 6+ years of hands-on experience in Data Engineering, ideally in AdTech, MarTech, Growth, consumer internet, or other high-scale / multi-product environments
  • Strong hands-on expertise in SQL, Python, Snowflake, and dbt
  • Proven experience designing and building modern data platforms at scale
  • Strong experience with:
    • batch and near-real-time data pipelines
    • streaming / event-driven architectures
    • modern data modeling and ELT patterns
    • Medallion architecture
    • data contracts and schema evolution
  • Proven experience modernizing complex, interconnected data systems with strong ownership
  • Experience building production-grade data systems that support BI, experimentation, product analytics, and ML use cases
  • Strong judgment across performance, scalability, reliability, and cost tradeoffs
  • Experience partnering cross-functionally with Data Science, BI, Product, Engineering, and business teams
  • Ability to guide teams toward an AI-first way of working, while maintaining strong validation and engineering discipline
  • Strong technical leadership and mentoring capability, with the ability to influence across teams without direct authority
  • Comfort operating in ambiguity and still driving systems into production
Nice to Have
  • Experience with Iceberg, Trino, Kafka, Kinesis, Apache Flink, or similar modern lakehouse / streaming technologies
  • Familiarity with feature stores, model-serving pipelines, and DataOps practices
  • Experience supporting experimentation platforms, self-serve BI, or performance marketing use cases
  • Experience in consumer rewards, surveys, monetization, or marketplace-style ecosystems
  • Experience with cloud-native data stacks and modern observability tooling
  • Familiarity with AI-assisted or AI-first development practices across data teams

Pay Transparency:
The anticipated base salary range for this position is $240,000 to $275,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Prodege Benefits:
Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.
Equal Employment Opportunity Statement
At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.
FCIHO
Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

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