Data Engineer Lead

Turtle Trax S.A.; United States; Hybrid; USD 140,000 - 180,000; Full time

Job summary

Turtle Trax S.A. is seeking a Lead Data Engineer to drive the development of scalable data platforms for on-prem and cloud environments. You will design end-to-end data pipelines, mentor engineers, and participate in architecture discussions to align with product goals.

The role emphasizes building robust, testable code and contributing to data governance while collaborating with cross-functional teams to deliver value across the business.

Qualifications

• Extensive experience building production-grade data pipelines on big data platforms.
• Strong Python, Spark and SQL skills with Hadoop ecosystem familiarity.
• Cloud data platform experience (Databricks, Snowflake) preferred.
• Proven ability to mentor engineers and participate in architecture reviews.

Responsibilities

• Design and build scalable, cloud-native data platforms for modern data engineering practices.
• Mentor and guide other engineers, sharing knowledge and code reviews.
• Create robust ETL/ELT pipelines for diverse systems and business-critical use cases.
• Lead by example with high-quality, testable code and architecture discussions.
• Decompose complex problems into modular, scalable components aligned with goals.
• Support data governance: lineage, cataloging, and access management integration.
• Participate in architectural discussions, planning, and feature sizing meetings.

Skills

Big data pipelines

Python

Spark

SQL

Data governance

Leadership

CI/CD

Java

Debugging complex data issues

Tools

Databricks

Snowflake

Hadoop

Hive

Impala

Airflow

NiFi

Talend

Git

Job description

Data Engineer Lead

Overview We are looking for a Lead Data Engineer who will help in implementing data analytics products using on-prem and cloud data platforms.

Position Responsibilities

• Design and build scalable, cloud-native data platforms for modern data engineering practices.
• Mentor and guide other engineers, sharing knowledge, reviewing code, and fostering a culture of curiosity, growth, and continuous improvement.
• Create robust, maintainable ETL/ELT pipelines that integrate with diverse systems and serve business-critical use cases.
• Lead by example—write high-quality, testable code and participate in architecture and design discussions with a long-term view in mind.
• Decompose complex problems into modular, efficient, and scalable components that align with platform and product goals.
• Support data governance and quality efforts, ensuring data lineage, cataloging, and access management are built into the platform.
• Participate in architectural discussions, iteration planning, and feature sizing meetings

SKILLS

• Strong hands-on experience in data engineering building production-grade pipelines on big data platforms (Hadoop ecosystem and cloud data platforms - databricks).
• High proficiency in using Python, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL to build Big Data products.
• Hands-on experience with cloud data platforms such as databricks, snowflake (databricks preferred)
• Experience with orchestration/integration tools such as Apache Airflow, Apache NiFi, or Talend.
• Working knowledge of DevOps/CI-CD practices: version control (Git), automated testing, release pipelines, and observability.
• Strong problem-solving skills with the ability to debug complex data issues and communicate clearly with technical and non-technical stakeholders.
• Experience developing Java based applications is an added advantage

hybrid GDL offices techM
remote