Senior Data Engineer

DTN•Austin, TX

18d

About The Position

We are seeking a Senior Data Engineer who possesses a strong drive for results. In this role, you will be responsible for ensuring the ingestion, quality, integrity, and reliability of our data engineering processes and outputs and helping lead key architecture change within DTN, while providing expert support to our customers and internal teams.

Requirements

Minimum 7 years of data engineering experience, with a strong background in pipelines, ingest, and ETL/ELT processes, and expert-level knowledge of databases, including Oracle and Postgres
Minimum 5 years and deep expertise in AWS cloud services and architecture
Advanced competency and extensive work experience with the following technical skills: Apache Airflow or other workflow tools PySpark, Amazon Elastic Map Reduce (EMR) Lakehouse architectures with AWS S3 Tables, LakeFormation, and Apache Iceberg Docker, Kubernetes Terraform, Liquibase, GitLab pipelines, source control and versioning using Git Data quality with tools like Great Expectations Python for data development (and ideally API & Web development) Advanced data preparation techniques using ETL / SQL processing Expert consuming both REST and GraphQL APIs

Nice To Haves

Geospatial processing with PostGIS and Apache Sedona
Deep experience deploying with Data Engineering best practices and a track record of implementing these
Deep experience processing and deploying large datasets efficiently
Deep technical understanding of relational and non-relational databases
A customer focus and understanding of who consumes the data downstream and the value it brings
A leadership mindset, leading change, mentoring others, working effectively across groups
Ability to work and thrive in a fast-paced environment, learn rapidly, and master diverse web technologies and techniques
Able to communicate effectively to a wide range of audiences and levels

Responsibilities

Lead and architect the delivery of trusted data sets and services from complex data sources and environments for DTN partners and customers.
Design and implement our modern data and analytic architecture, establishing best practices for data management, integration, and acquisition patterns and pipelines.
Provide expert-level support to DTN partners and customers, solving complex technical issues with data infrastructure and environments.
Drive continuous improvement initiatives for data management practices, patterns, and standards across the organization.
Develop and maintain comprehensive documentation for data engineering practices and standards, promoting broader adoption and consistency across teams.
Oversee and ensure DTN's data governance and security practices are implemented at the highest standards.
Lead initiatives to identify and improve internal processes by designing innovative data management and infrastructure solutions that enhance capabilities, reduce costs and complexity, and drive automation.
Architect and develop enterprise-wide reference documentation, patterns, SODs, and reference architectures that enable specific fit-for-purpose needs and set the overall direction in the Data and Analytics domain.
Mentor junior data engineers and provide technical leadership to cross-functional teams.

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