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Data Engineer 500K Jobs (NOW HIRING)

TriOptus LLC

Data Analyst - IT III

Chicago, IL · On-site

... 500K of customers a day and our operation is complex 3. PowerBI 4. Independent with minimal ... This is not a PowerBI developer role. Required Skills : Data Analysis,SQL Basic Qualification

Wunderlich-Malec Engineering, Inc

Controls Engineer

Austin, TX · Hybrid

$82K - $107K/yr

... data center building automation * Will act as technical lead on projects and guide lower level engineers and technicians * Will act as Project Manager on projects up to $500k. This includes but not ...

Linde

Electrical Reliability Engineer

Magna, UT · On-site

Analyze equipment performance data to ensure optimal operation of regional electrical assets ... Serve as the regional electrical maintenance engineer supporting the Magna, UT facility and ...

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How much do data engineer 500k jobs pay per year?

As of Jul 10, 2026, the average yearly pay for data engineer 500k in the United States is $147,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $196,000.00 per year, depending on experience, location, and employer.

What is a Data Engineer 500K job?

A Data Engineer 500K job typically refers to a high-paying data engineering role, often at top tech companies, hedge funds, or startups, where total compensation (salary, bonuses, and stock options) reaches $500,000 or more. These roles usually require strong expertise in data infrastructure, ETL pipelines, cloud platforms, and big data technologies. Candidates often have years of experience in software engineering, distributed systems, and working with large-scale datasets. High-paying Data Engineer roles are common in industries like finance, AI, and big tech, where data efficiency directly impacts business success.

What are the key skills and qualifications needed to thrive in the Data Engineer 500K position, and why are they important?

To thrive as a Data Engineer 500K, you need a solid background in computer science, expertise in designing data architectures, and advanced proficiency with programming languages such as Python or Java, often supported by a related degree or equivalent experience. Familiarity with big data frameworks (e.g., Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and certifications in these tools are highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills distinguish top performers in this field. These competencies collectively enable Data Engineers to build robust, scalable data systems that drive business insights and operational efficiency.

What are the main challenges Data Engineers face in high-compensation roles such as this one?

Data Engineers in high-compensation roles like this often work on complex, large-scale data infrastructure projects that require not only technical expertise but also the ability to adapt quickly to evolving technologies. One common challenge is optimizing data pipelines for both performance and reliability while managing massive volumes of data from diverse sources. Additionally, close collaboration with data scientists, engineers, and business stakeholders is necessary to understand data requirements and ensure high-quality, accessible datasets. Success in this environment depends on staying up to date with new tools, embracing continuous learning, and adeptly balancing immediate project needs with long-term architectural considerations.

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Data Engineer 500K jobs near you

Senior Consultant, Data Engineering & Analytics

Castleton Tower

New York, NY • Remote

$250K - $500K/yr

Full-time

Re-posted 12 days ago

Job description

The Firm

Castleton Tower is a boutique consulting firm founded by executives who have built and led quantitative research, data science, and technology teams at top-tier hedge funds and asset managers. We work exclusively with investment management firms (RIAs, family offices, hedge funds, and asset allocators) helping them modernize their data infrastructure and build AI-ready foundations.

What makes us different: We're a lean firm where senior practitioners do the actual work. No armies of junior consultants learning on your dime. Our engagements blend high-level strategy with hands-on technical implementation. We'll assess your technical & business strategy, design your data architecture and also code up the full stack infrastructure where needed.

The Opportunity

We're looking for a technical leader who can design and build data platforms for investment firms. This role emphasizes hands-on engineering while maintaining strategic client engagement. You'll architect data warehouses, build production pipelines, and develop quantitative tools that directly support investment decisions.

What you'll get:

  • Strategic Impact: Lead full-scope projects from architecture design to production deployment

  • Direct Mentorship: Work alongside the firm's Principals on every engagement

  • Modern Tech Stack: Work with best-in-class tools (Snowflake, Databricks, dbt, Dagster, cloud infrastructure, etc.) and cutting-edge AI/agentic development workflows

  • Path to Partnership: Clear trajectory toward firm equity and partnership for high performers

Core Responsibilities

Technical Leadership

  • Lead the design and implementation of scalable data platforms (data warehouses, data lakes) and end-to-end data pipelines

  • Develop and optimize production-grade code (Python/Spark) for data transformation and financial analysis

  • Build customized analytical applications, dashboards, and quantitative investment tools

  • Ensure efficient delivery and adherence to data governance and integrity standards

Client Engagement

  • Collaborate with client investment teams to translate investment process requirements into robust, automated tools and data products

  • Provide technical and project leadership across engagements

  • Understand client business context to ensure technical solutions solve real problems

Qualifications

Required:

  • 7+ years of hands-on experience in a technical or analytical role (Quant, Quant Dev, Data Scientist, or Data Engineer). Minimum of 5 years for highly exceptional candidates

  • Prior experience at hedge funds, fintech firms/startups, market makers, or top-tier asset management firms. Experience at top technology or strategy consulting firms considered on a case-by-case basis

  • Demonstrated project leadership, ideally overseeing technical delivery from inception to production

  • Proficiency in Python (Pandas, NumPy, Scikit-learn) and advanced SQL query optimization

  • Experience with at least one major cloud platform (AWS, GCP, or Azure) and associated data services (Snowflake, Databricks)

  • Deep understanding of data modeling and data warehousing principles

Valued:

  • Familiarity with data pipeline orchestration tools (Airflow, Dagster, Prefect)

  • Experience building quantitative trading or investment tools

  • Background in financial data (market data, portfolio analytics, fund accounting)

Personal Attributes:

  • High ownership mentality: you see problems through to resolution without being told

  • Understands what high-quality work looks like and how to deliver it

  • Curious and interested in learning about new technologies and the investment industry

  • Seeks to understand the broader business context, not just the technical requirements

  • Independent thinker who takes initiative

Location & Compensation

Location: Hybrid in the NYC area. Expect to travel roughly one week per month for on-site client work.

Compensation:

  • Total expected compensation: $250 to $500K+ (commensurate with experience)

  • Firm equity available for high performers

Compensation Range: $250K - $500K