Sr. Data Engineer

For decades, DTN has been the silent force behind some of the world’s most critical industries—helping businesses navigate complexity, uncertainty, and risk with smarter, faster decisions. From agriculture to energy to weather intelligence, our proprietary Operational Decisioning Platform transforms raw data into decision-grade insights—enabling companies to optimize supply chains, ensure market stability, and safeguard infrastructure against disruption. We don’t follow trends—we set the standard for precision, trust, and operational impact.

DTN is at an exciting inflection point. Building off a foundation of financial strength, profitability, and industry trust, we’re accelerating growth and expanding our global footprint. Our purpose-built solutions—powered by AI and honed by decades of vertical expertise—are helping some of the world’s most significant enterprises thrive amid operational constraints and uncover new opportunities in a fast-changing world.

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Description:

Job Description: DTN is seeking a results-driven Sr. Data Engineer to support the ingestion, quality, integrity, reliability, and governance of data across our enterprise platforms. This role plays a critical part in advancing DTN’s modern batch and real-time streaming data architecture while enabling customers and internal stakeholders to leverage trusted, scalable, and secure data solutions.

The ideal candidate brings expert experience in data engineering, cloud technologies, streaming data, and software development, along with a passion for building high-quality data pipelines, improving processes, and supporting data-driven decision-making across the organization.

What You Will Be Responsible For

Deliver trusted data sets and services from complex data sources and environments to support DTN customers and internal stakeholders Support the development and delivery of modern data and analytics architecture through batch and streaming data integration, acquisition, and management solutions Design, build, and maintain batch and real-time streaming data pipelines and ingestion processes that ensure data quality, reliability, and scalability Architect and manage high-throughput event streaming solutions utilizing Apache Kafka and Amazon Kinesis Support customer and partner data infrastructure needs by troubleshooting technical issues and optimizing data environments Contribute to the continuous improvement of data management standards, practices, and architectural patterns Document data engineering processes, standards, and best practices to promote adoption across teams Ensure data governance, security, and compliance requirements are incorporated into solution delivery Identify opportunities to automate processes, reduce complexity, and improve operational efficiency through innovative data solutions

Develop reference architectures, standards, and documentation to support consistent approaches to data acquisition, transformation, storage, and analytics consumption

What You Will Bring to the Position

7+ years of data engineering experience with batch and streaming pipelines, data ingestion, ETL/ELT processes, or 2+ years of software engineering experience Proven experience designing and implementing streaming data architectures, message brokering, and real-time event processing using Apache Kafka and AWS Kinesis 4+ years of cloud experience, preferably across multiple cloud platforms Strong programming skills in Python or other modern development languages such as Java or Go

Experience with ETL processes, SQL development, and data transformation workflows Experience working with relational databases such as Oracle, PostgreSQL, or MySQL

Experience with AWS cloud services and cloud-based data platforms such as Snowflake…