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Senior Data Engineer

Remote - USA · Incline Village, Nevada, United States

Pay
Salary not listed in the saved posting
Work setup
Remote — work setup source
Location type: Remote
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Tech — team source

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
As a note; Socure cannot provide sponsorship now or in the future for this role.
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What you’ll work on

Full posting

We are looking for a Senior Data Engineer to join our Data Automation team.

  • Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains.

  • Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation.

  • Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies.

From the employer’s posting
We are looking for a Senior Data Engineer to join our Data Automation team. You will play a critical role in designing and building scalable data platforms and pipelines that power Socure’s identity verification products and analytics. This role is ideal for someone who has a strong passion for solving real business problems with data, and combines deep hands-on data engineering expertise with strong ownership.
What You'll Do Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains. Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation.
Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains. Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation. Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies.
Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation. Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies. Automate data operations (validation, quality checks, alerting, backfills, and recovery workflows) to reduce manual effort and improve consistency.

What you’ll bring

All qualifications

Core experience

  • 5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines.
  • Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.
  • Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).
  • Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.
  • Experience operating and supporting production pipelines, including monitoring, alerting, incident response, and improving reliability over time.
  • Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.

Preferred experience

  • Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc).
  • Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).
  • Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.
  • Experience with prompt engineering using modern GenAI, Large Language Models (LLM).
Qualification wording
5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines.
Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.
Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).
Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.
Experience operating and supporting production pipelines, including monitoring, alerting, incident response, and improving reliability over time.
Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc).
Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).
Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.
Experience with prompt engineering using modern GenAI, Large Language Models (LLM).

Tools in this posting

  • Python
  • Scala
  • SQL
  • AWS
  • Kafka
  • S3
  • Spark
  • Airflow
Source — Tool mentions in context
• 5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines. • Strong programming skills in general-purpose language (such as Python or Scala) for data processing, and SQL for data analytics. • Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.
• Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization. • Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc). • Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.
Preferred Qualifications • Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc). • Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).
• Strong programming skills in general-purpose language (such as Python or Scala) for data processing, and SQL for data analytics. • Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization. • Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).
• Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc). • Hands-on experience with data orchestration tools (Airflow, Step Functions, etc). • Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.

Job description

View original posting ↗

Why Socure?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.

About the Role

We are looking for a Senior Data Engineer to join our Data Automation team. You will play a critical role in designing and building scalable data platforms and pipelines that power Socure’s identity verification products and analytics. This role is ideal for someone who has a strong passion for solving real business problems with data, and combines deep hands-on data engineering expertise with strong ownership.

What You'll Do

• Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains.

• Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation.

• Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies.

• Automate data operations (validation, quality checks, alerting, backfills, and recovery workflows) to reduce manual effort and improve consistency.

• Optimize cost, performance, and reliability of data workloads.

• Partner closely with cross-functional teams (Data Science, Product, Engineering) to understand requirements, translate them into technical solutions.

• Evaluate and adopt new technologies (new processing engines, storage formats, orchestration tools, GenAI-assisted ingestion) to keep the platform modern and efficient.

What You Bring

• 5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines.

• Strong programming skills in general-purpose language (such as Python or Scala) for data processing, and SQL for data analytics.

• Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.

• Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).

• Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.

• Experience operating and supporting production pipelines, including monitoring, alerting, incident response, and improving reliability over time.

• Solid foundation in software engineering practices, including version control, CI/CD, testing strategies, and code review.

• Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.

Preferred Qualifications

• Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc).

• Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).

• Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.

• Experience with prompt engineering using modern GenAI, Large Language Models (LLM).

• Experience mentoring other engineers and contributing to engineering-wide standards, best practices.

As a note; Socure cannot provide sponsorship now or in the future for this role.

Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.



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Pay

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Location & working pattern

Incline Village, Nevada, United States

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Work authorization
• Experience mentoring other engineers and contributing to engineering-wide standards, best practices. As a note; Socure cannot provide sponsorship now or in the future for this role. Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.
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Last seen by us
Sep 25, 2026
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Mar 26, 2026

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