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Temporal Software Engineer Jobs in Prosper, TX (NOW HIRING)

Programmers.io

Snowflake Developer

Dallas, TX · On-site

Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices ... Temporal Data Modeling: Managing state changes over time (e.g., SCD Type 2). b. c. d. Schema ...

Judge Group, Inc.

Network Automation Engineer

Irving, TX · On-site

$65 - $72/hr

... software engineering practices. This role is part of a dedicated automation initiative, with ... Create stateful workflow orchestration using Temporal, ORCA, or similar technologies * Integrate ...

Further

Senior Software Developer

Dallas, TX · Hybrid

$54 - $71.25/hr

... engineer who can take a hard problem from data layer to UI to model gateway and back without ... Drizzle ORM, Temporal, or Redpanda/Kafka in production. * OpenTelemetry beyond surface-level ...

Further

Senior Software Developer

Dallas, TX · Hybrid

$54 - $71.25/hr

... engineer who can take a hard problem from data layer to UI to model gateway and back without ... Drizzle ORM, Temporal, or Redpanda/Kafka in production. * OpenTelemetry beyond surface-level ...

Further

Senior Software Developer

Dallas, TX · On-site

$54 - $71.25/hr

... engineer who can take a hard problem from data layer to UI to model gateway and back without ... Drizzle ORM, Temporal, or Redpanda/Kafka in production. * OpenTelemetry beyond surface-level ...

Wells Fargo

Senior Automation Network Engineer

Irving, TX · Hybrid

$99K - $131K/yr

Success in this role requires a platform mindset, strong software engineering discipline, and prior ... Hands-on experience with workflow orchestration platforms (Temporal, ORCA, or similar) * Strong ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

... temporal mapping. - Decompose mining workflows into structured task sequences, labeling actions ... Desired (Nice to Have): - Background in Mining Engineering, Robotics, Autonomous Vehicles, or ...

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Showing results 21-40

All JobsTemporal Software Engineer JobsTemporal Software Engineer Jobs in Prosper, TX

Temporal Software Engineer information

See Prosper, TX salary details

$58.2K

$135.1K

$188.2K

How much do temporal software engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for temporal software engineer in Prosper, TX is $135,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,900.00 and $158,400.00 per year, depending on experience, location, and employer.

What is a Temporal Software Engineer?

A Temporal Software Engineer is a developer who specializes in building, maintaining, and optimizing applications using the Temporal open-source workflow orchestration platform. Temporal enables engineers to manage complex, long-running, and distributed workflows in a reliable and scalable way. Temporal Software Engineers typically design workflows, implement fault-tolerant logic, and help teams automate business processes that require reliability and durability. Their expertise ensures that workflows can recover from failures, maintain state, and handle retries without losing data or process integrity.

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

To thrive as a Temporal Software Engineer, you need strong software engineering fundamentals, proficiency in distributed systems concepts, and experience with languages like Go, Java, or TypeScript. Familiarity with Temporal's workflow orchestration platform, cloud infrastructure tools, and CI/CD systems is typically expected. Excellent problem-solving, collaboration, and communication skills help in designing resilient workflows and working with cross-functional teams. These skills are crucial for building reliable, scalable solutions that leverage Temporal for complex business processes.

What are some common challenges faced by Temporal Software Engineers when designing workflows, and how can they be addressed?

Temporal Software Engineers often encounter challenges such as managing complex workflow dependencies, handling failure recovery, and ensuring workflow scalability. These challenges can be addressed by leveraging Temporal’s robust retry mechanisms, designing idempotent activities, and breaking workflows into smaller, reusable components. Collaboration with DevOps and QA teams is also crucial to ensure workflows are resilient and thoroughly tested in distributed environments.

What is the difference between Temporal Software Engineer vs Cloud Software Engineer?

AspectTemporal Software EngineerCloud Software Engineer
Required CredentialsBachelor's in CS or related, experience with Temporal SDKsBachelor's in CS or related, cloud platform certifications (AWS, Azure)
Work EnvironmentDeveloping distributed, event-driven applications using TemporalDesigning and deploying cloud-based solutions across platforms
Industry UsageTech companies implementing workflow orchestrationBroad industry use, including SaaS, enterprise, and startups
Search & Comparison IntentFocus on Temporal-specific skills and workflowsBroader cloud infrastructure and deployment skills

In summary, a Temporal Software Engineer specializes in building and maintaining workflow orchestration using Temporal, while a Cloud Software Engineer works on deploying and managing cloud-based applications across various platforms. Both roles require strong programming skills, but their focus areas differ significantly.

How much does a Temporal Software Engineer make?

A Temporal Software Engineer's salary typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Skilled engineers with expertise in distributed systems and workflow orchestration tools like Temporal are often compensated at the higher end of this range.

What are popular job titles related to Temporal Software Engineer jobs in Prosper, TX?

For Temporal Software Engineer jobs in Prosper, TX, the most frequently searched job titles are:

What cities near Prosper, TX are hiring for Temporal Software Engineer jobs?

Cities near Prosper, TX with the most Temporal Software Engineer job openings:

Temporal Software Engineer jobs near you

Engineering-L2-Dallas-Analyst-Software Engineering

Goldman Sachs, Inc.

Dallas, TX • On-site

Full-time

Posted 23 days ago

Goldman Sachs rating

7.8

Company rating: 7.8 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

88th of 171 rated banks

Job description


The Opportunity
At Goldman Sachs, engineering teams are positioned at the center of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform.
This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases, and may also help extend platform tooling where additional functionality is needed.
Role Summary
As a Software Engineer in the Data Platform team, you will design, build, test and support data pipelines and curated datasets on the firm's modern data platform. You will work across ingestion, transformation, modelling, optimization and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. Where there are gaps in platform functionality, you may also contribute to shared tooling or framework components that improve how the platform is used and operated.
The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases.
Key Responsibilities
Pipeline Engineering
  • Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
  • Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
  • Where needed, build reusable tooling to improve delivery, consistency and operational support.
  • Ensure data pipelines are production-ready, well tested and operationally supportable.

Data Modelling and Curation
  • Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
  • Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
  • Work with consumers to shape data products that are usable, well documented and aligned to business needs.

Data Quality and Reconciliation
  • Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
  • Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
  • Contribute to clear standards for testing, monitoring and issue resolution.
  • Contribute to practical improvements in testing, monitoring or reconciliation tooling where these strengthen platform reliability and day-to-day delivery.

Delivery and Partnership
  • Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations.
  • Communicate clearly on progress, risks, dependencies and design choices, including where delivery would benefit from improvements to shared platform tooling.

Skills and Experience
Required
  • Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
  • Strong hands-on programming experience in Python or Java.
  • Good working knowledge of SQL, including troubleshooting, optimization and data analysis.
  • Ability to learn new tools, internal platforms and delivery workflows quickly.
  • Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.

Data Engineering Capability
  • Understanding of temporal data modelling, including the handling of historical state and change over time.
  • Knowledge of schema design, schema evolution and data compatibility considerations.
  • Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
  • Ability to make sensible design choices across normalized and deformalized models, and between natural and surrogate keys.
  • Practical approach to data quality, reconciliation and root-cause analysis.
  • Experience building or supporting production data pipelines in a collaborative engineering environment.
  • Experience working with distributed data processing frameworks such as Apache Spark.
  • Working knowledge of common data formats such as JSON, Avro and Parquet.

For More Experienced Candidates
  • Stronger ownership of technical design across multiple datasets or pipeline domains.
  • Experience guiding implementation standards, code quality and engineering practices within a team.
  • Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers.

Technology Environment
The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies.
Examples of technologies in scope include:
  • Data processing and logic: ANSI SQL, Apache Spark, Kafka
  • Data formats: JSON, Avro, Parquet
  • Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ
  • Engineering and deployment: CI/CD tooling, containerized or Kubernetes-based deployment approaches where relevant

You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.
What We Are Looking For
We are looking for engineers who can deliver well-structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast-paced environment where data platforms support important business outcomes. It will also suit candidates who are willing to contribute to shared tooling or platform components that make the wider engineering environment more effective.
Stronger candidates will typically demonstrate:
  • sound judgement in technical trade-offs
  • attention to detail in data correctness and testing
  • a clear and structured approach to problem solving
  • willingness to work closely with stakeholders and partner teams
  • an ability to identify when delivery problems would be better solved through reusable tooling or platform improvements
  • an interest in developing long-term expertise within the firm

What Goldman Sachs employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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