Senior Data Engineer

Turtle Trax S.A.; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Turtle Trax S.A. is seeking a Senior Data Engineer to design, build, test, and maintain scalable data pipelines and data products supporting Enterprise Credit Risk initiatives.

You will work with Databricks, Spark, PySpark, Hadoop, SQL, and Python to deliver batch and real-time processing solutions across cloud-native platforms. You will partner with Risk, Product, Data Science, and Engineering teams to translate business requirements into robust technical solutions, develop reusable frameworks,

Qualifications

• Design and maintain enterprise-scale data pipelines and products.
• Experience with cloud and lakehouse technologies in production.
• Strong SQL, Python, and data modeling fundamentals.

Responsibilities

• Design, develop, test, and maintain scalable data pipelines and data products.
• Build batch and real-time processing solutions in cloud environments.
• Collaborate with Risk, Product, Data Science and Engineering teams to translate requirements.
• Develop reusable frameworks and patterns for platform consistency.
• Implement data quality controls, monitoring, and observability.
• Support migration to Databricks and cloud-native platforms.
• Build curated datasets for lending decisions and risk analytics.
• Participate in architecture discussions and provide technical recommendations.
• Troubleshoot production issues and drive root-cause analysis.
• Follow code quality, testing, deployment, security, and ops best practices.
• Mentor junior engineers and share knowledge.
• Continuously improve scalability, performance, and cost-efficiency.

Skills

Enterprise data engineering

Databricks

Apache Spark

Python

SQL

Data modeling

CI/CD

DevOps practices

Airflow

Problem solving

Mentoring

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related STEM field

Tools

Databricks

Apache Spark

PySpark

Hadoop

Delta Lake

Azure Data Services

Data Factory

Kafka

GitHub

AirFlow

Job description

Senior Data Engineer

Role

As a Senior Data Engineer, you will:

• Design, develop, test, and maintain scalable data pipelines and data products supporting Enterprise Credit Risk initiatives.
• Build and optimize batch and real-time data processing solutions using modern cloud and lakehouse technologies.
• Partner with Risk, Product, Data Science, and Engineering teams to understand business requirements and translate them into technical solutions.
• Develop reusable frameworks, components, and engineering patterns that improve development efficiency and platform consistency.
• Implement data quality controls, monitoring, alerting, and observability capabilities to ensure data reliability and trustworthiness.
• Support the migration and modernization of existing data assets and workloads into Databricks and cloud-native platforms.
• Build and maintain curated datasets that support lending decisioning, portfolio risk management, and advanced analytics use cases.
• Participate in architecture discussions and contribute technical recommendations for platform enhancements.
• Troubleshoot production issues and drive root cause analysis to improve platform reliability and performance.
• Follow engineering best practices for code quality, testing, deployment automation, security, and operational excellence.
• Mentor junior engineers through code reviews, technical guidance, and knowledge sharing.
• Continuously evaluate opportunities to improve scalability, performance, cost efficiency, and maintainability of data platforms.

All About You

Essential Skills & Experience

• Strong experience developing and maintaining enterprise-scale data engineering solutions.
• Hands‑on experience with Databricks, Apache Spark, PySpark, Hadoop, SQL, and Python.
• Experience building ETL/ELT pipelines and large-scale data processing applications.
• Experience working with cloud‑based data platforms and storage technologies.
• Strong understanding of data modeling concepts and analytical data structures.
• Experience implementing automated testing, monitoring, and data quality practices.
• Experience with Data formats ( Parquet, Avro, ORC )
• Knowledge of CI/CD pipelines, Git-based development workflows, and DevOps principles.
• Experience with Workflow orchestration Tools like Airflow
• Strong analytical and problem‑solving skills with the ability to work independently on complex technical challenges.
• Effective communication skills with the ability to collaborate across technical and business teams.
• Experience mentoring or supporting less experienced engineers.
• Knowledge of Java Based application development is a huge Plus.

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related STEM field or alternative minimum of 5 years of experience in a related field.

Technical Skills

Experience with several of the following technologies:

• Databricks
• Apache Spark / PySpark
• AirFlow
• SQL
• Python
• Delta Lake
• Azure Data Services
• Data Factory or equivalent orchestration tools
• Kafka or streaming platforms
• GitHub
• CI/CD automation
• Data Quality and Observability tools

ADVANCED ENGLISH

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