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Associate Data Engineering Jobs in Richardson, TX

AI Engineering Associate Director We are seeking an experienced AI Engineer to design, build, test ... Partner with solution architects, data scientists, cloud engineers, software developers, and ...

Data Protection Associate

Coppell, TX · On-site

$54K - $55K/yr

Being a member of IT Cybersecurity & Platform Engineering team, the Data Protection Operations Associate is responsible for the day-to-day operation of DTCC's data protection controls, with primary ...

Data Protection Associate

Dallas, TX · On-site

$58K - $59K/yr

Being a member of IT Cybersecurity & Platform Engineering team, the Data Protection Operations Associate is responsible for the day-to-day operation of DTCC's data protection controls, with primary ...

Data Engineer

Grand Prairie, TX · On-site

$109K - $131K/yr

This is a hands-on engineering role focused on building reliable data pipelines, processing large ... Relocation assistance Oscar Associates Limited (US) is acting as an Employment Agency in relation ...

In data engineering at PwC, you will focus on designing and building data infrastructure and ... Associate] is a plus - Designing and implementing thorough data architecture strategies ...

Data Engineer - Senior Manager

Dallas, TX · On-site

$124K - $280K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and ... Associate] is a plus - Designing and implementing thorough data architecture strategies ...

Showing results 41-60

Associate Data Engineering information

See Richardson, TX salary details

$13

$30

$51

How much do associate data engineering jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for associate data engineering in Richardson, TX is $30.04, according to ZipRecruiter salary data. Most workers in this role earn between $22.26 and $35.58 per hour, depending on experience, location, and employer.

What is an associate data engineer?

An Associate Data Engineer is an entry-level professional who assists in designing, building, and maintaining data pipelines and infrastructure. They typically work with senior data engineers to ensure data is collected, stored, and processed efficiently for analytics and business use. Responsibilities often include data cleaning, integration, and supporting the development of scalable data solutions. Associate Data Engineers usually have foundational knowledge of programming, databases, and cloud technologies.

What are some typical projects an associate data engineer might work on in their first year?

In their first year, an Associate Data Engineer often works on building and maintaining data pipelines, cleaning and transforming raw data, and supporting the integration of new data sources. They may also assist in optimizing existing data workflows for better performance and reliability, as well as collaborating closely with data analysts and senior engineers to ensure data quality and accessibility. These projects help new team members develop a strong understanding of the organization's data infrastructure and best practices in data engineering.

What are the key skills and qualifications needed to thrive as an associate data engineer, and why are they important?

To thrive as an Associate Data Engineer, a solid understanding of database systems, SQL, data modeling, and a relevant bachelor's degree in computer science or a related field is essential. Familiarity with ETL tools, cloud platforms like AWS or Azure, and programming languages such as Python or Java is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help set candidates apart in collaborative, data-driven environments. These skills and qualities are crucial for building reliable data pipelines, ensuring data quality, and enabling actionable business insights.

What is the difference between Associate Data Engineering vs Data Engineer?

AspectAssociate Data EngineeringData Engineer
Required CredentialsBachelor's degree in CS, IT, or related field; some certificationsBachelor's or master's degree; extensive experience preferred
Work EnvironmentEntry-level, team-focused, supporting data pipelinesDesigning, building, and maintaining large-scale data systems
Employer & Industry UsageCommon in tech companies, finance, healthcareUsed across industries for advanced data infrastructure roles
Search & Comparison IntentEntry-level, learning, support rolesAdvanced, specialized data infrastructure roles

The main difference between Associate Data Engineering and Data Engineer lies in experience and responsibilities. Associate Data Engineers are typically entry-level, focusing on supporting data pipelines and gaining hands-on experience. Data Engineers have more experience, handling complex data architecture, optimization, and system design. Both roles require similar educational backgrounds, but Data Engineers usually have more technical expertise and responsibility.

What are the most commonly searched types of Data Engineering jobs in Richardson, TX?

The most popular types of Data Engineering jobs in Richardson, TX are:

What are popular job titles related to Associate Data Engineering jobs in Richardson, TX?

For Associate Data Engineering jobs in Richardson, TX, the most frequently searched job titles are:

What job categories do people searching Associate Data Engineering jobs in Richardson, TX look for?

The top searched job categories for Associate Data Engineering jobs in Richardson, TX are:

What cities near Richardson, TX are hiring for Associate Data Engineering jobs?

Cities near Richardson, TX with the most Associate Data Engineering job openings:

Infographic showing various Associate Data Engineering job openings in Richardson, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $62,475 per year, or $30 per hour.

Engineering - Dallas - Associate, Security Engineering - 10427751

Goldman Sachs

Dallas, TX

Full-time

Posted 27 days ago


Key responsibilities

  • Design, develop, and maintain scalable data ingestion and processing pipelines for security data.

  • Build and optimize batch and streaming workflows to ensure timely delivery of security event data and telemetry.

  • Develop and support data models, schemas, and data warehouse structures to organize and analyze high-volume event data.


Goldman Sachs rating

7.8

Company rating: 7.8 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

88th of 175 rated banks


Job description

Job Duties: Associate, Security Engineering with Goldman Sachs Services LLC in Dallas, Texas. Design, develop, and maintain scalable data ingestion and processing pipelines to collect, transform, enrich, and load large volumes of structured and semi-structured data from diverse sources into a centralized big data platform, enabling the organization to detect and analyze malicious cyber threats and anomalous activity across its infrastructure. Develop and optimize both batch and streaming data processing workflows to ensure timely and reliable delivery of security event data and telemetry to downstream analytics systems, supporting real-time alerting and incident response capabilities. Design and implement data models, schemas, and data warehouse structures to organize and correlate high-volume event data from multiple sources, supporting analytical reporting, data science initiatives, and operational decision-making. Build and maintain data quality monitoring frameworks, alerting systems, and observability dashboards to ensure pipeline reliability, accuracy, completeness, and performance, guaranteeing that critical data streams remain uninterrupted for continuous monitoring. Develop and maintain Continuous Integration and Continuous Deployment (CI/CD) pipelines to automate the testing, building, and deployment of data engineering applications and infrastructure components, ensuring rapid and reliable delivery of platform updates. Deploy, administer, and scale data systems and infrastructure across on-premises data centers and Amazon Web Services (AWS) cloud environments using container orchestration tools such as Kubernetes to support high-availability, fault-tolerant data processing at scale. Research, evaluate, and implement best-in-class data engineering tools and technologies by conducting Proof-of-Concept activities and recommending solutions that improve platform capabilities, scalability, and efficiency. Collaborate with cross-functional teams - including threat management, detection engineering, data science, and analytics teams - to gather data requirements, define data contracts, and ensure data streams are effectively configured and monitored. Coordinate with product owners and third-party vendor support teams to elicit technical requirements and resolve platform issues. Participate in architecture and design discussions to develop solutions that advance the organization's data infrastructure and analytical maturity for processing and analyzing large-scale enterprise telemetry data.

Job Requirements: Master's degree (U.S. or foreign equivalent) in Cyber Security, Computer Engineering, Data Science and Analytics, or a related field and one (1) year of experience in the job offered or a related security or data engineering role OR Bachelor's degree (U.S. or foreign equivalent) in Cyber Security, Computer Engineering, Data Science and Analytics, or a related field and three (3) years of experience in the job offered or a related security or data engineering role. Prior work experience must include one (1) year of experience (with a Master's degree) or three (3) years of experience (with a Bachelor's degree) with each of the following: designing, deploying, and maintaining data pipeline systems and ingestion frameworks across on-premise and cloud environments; implementing and supporting distributed data technologies such as Spark, Kafka, Kubernetes, and BigQuery or similar for real-time and batch data processing and analysis; developing automation and tooling using Python to support data monitoring, enrichment, and platform engineering workflows; building and supporting ETL and data ingestion pipelines to centralize large-scale event data into scalable big data infrastructure; implementing and administering AWS cloud infrastructure to enable reliable data processing and analytics capabilities; and collaborating cross-functionally with engineering, analytics, and data science teams to ensure systems and data streams are effectively configured and monitored.

The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.


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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869