Senior Data Engineer

Syngenta Group•Durham, NC

16h•$114,100 - $163,000•Hybrid

About The Position

We're looking for a Senior Data Engineer to join our team in Durham, United States. In this role, you will design, build, and maintain scalable data infrastructure and pipelines that support our organization's data-driven decision-making. You will work with cross-functional teams to understand data requirements, architect robust solutions, and optimize data systems for performance and reliability. The ideal candidate will be detail-oriented, analytical, and organized, with a proven ability to manage complex data engineering projects from conception to production.

Requirements

5+ years of professional experience in data engineering or a related field
Advanced proficiency in at least two programming languages (Python, Java, Scala, or similar)
Strong expertise in SQL and relational/non-relational database management
Demonstrated experience designing and implementing large-scale data pipelines and ETL processes
Hands-on experience with cloud data platforms (AWS, Azure, or GCP)
Proficiency with big data technologies such as Apache Spark and Hadoop
Experience with version control systems (Git) and collaborative development workflows
Strong understanding of data modeling, database architecture, and optimization techniques
Experience with containerization and orchestration tools (Docker, Kubernetes)
Familiarity with CI/CD tools and practices for automated testing and deployment
Excellent problem-solving skills and ability to work independently and as part of a team
Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders

Nice To Haves

Experience with streaming technologies (Apache Kafka, Flink)
Knowledge of machine learning frameworks and data science workflows
Experience with data warehousing solutions (Snowflake, BigQuery, Redshift)

Responsibilities

Design and develop scalable data pipelines and ETL processes to ingest, transform, and load data from multiple sources
Architect and maintain data infrastructure on cloud platforms (AWS, Azure, or GCP) to ensure high availability and performance
Write clean, efficient, and well-documented code in programming languages such as Python, Java, or Scala
Optimize database queries and data models to improve system performance and reduce latency
Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver solutions that meet business objectives
Implement and manage big data technologies including Apache Spark, Hadoop, and related frameworks
Establish and enforce data quality standards, monitoring, and validation processes
Conduct code reviews and mentor junior engineers to maintain high code quality standards
Troubleshoot and resolve data pipeline issues, ensuring minimal downtime and data integrity
Document technical designs, architecture decisions, and operational procedures for knowledge sharing