Senior Data Engineer, Data Platform & Pipelines

Socure; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Socure is seeking a Senior Data Engineer to join the Data Automation team in the United States. You will design and build scalable data platforms and pipelines powering identity verification products and analytics, combining hands-on data engineering with strong ownership.

The role emphasizes end-to-end delivery, cloud-native data platforms, and collaboration with Data Science, Product, and Engineering to solve complex business problems with data at scale.

Qualifications

• 5+ years of hands-on data engineering experience building production data platforms.
• Proficient in Python or Scala and SQL for data processing and analytics.
• Deep experience with distributed processing frameworks like Apache Spark.
• Experience with AWS data services (EMR, Lambda, S3) and data warehousing.
• Strong data modeling and partitioning for large datasets.
• Experience with monitoring, reliability, and incident response of pipelines.

Responsibilities

• Design and build batch and streaming pipelines for ingestion, feature engineering, and analytics.
• Own end-to-end delivery of complex data initiatives including architecture, tests, deployment, and docs.
• Evolve the data platform with cloud-native technologies for scale and efficiency.
• Automate data operations: validation, quality checks, alerting, backfills, recovery.
• Collaborate with Data Science, Product, and Engineering to translate requirements into solutions.
• Evaluate new tech (Spark engines, orchestration, GenAI-assisted ingestion) to keep platform modern.

Skills

Python

SQL

Scala

Distributed data processing

Data modeling

Communication skills

Tools

AWS EMR

AWS Lambda

Amazon S3

Airflow

Kafka

Kinesis

Step Functions

GenAI

Job description

Socure is seeking a Senior Data Engineer to join the Data Automation team in the United States. You will design and build scalable data platforms and pipelines powering identity verification products and analytics, combining hands-on data engineering with strong ownership.

The role emphasizes end-to-end delivery, cloud-native data platforms, and collaboration with Data Science, Product, and Engineering to solve complex business problems with data at scale.