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# Sr Data Engineer

- **Company:** Transamerica Corporation
- **Location:** Cedar Rapids, IA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Amazon Web Services, Data Analysis, Big Data, Cloud Computing, Continuous Delivery, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Profiling, Data Visualization, Data Warehousing, Linux, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, Metadata, Node.Js, Reference Data, Scala (Programming Language), Shell Script, Software Engineering, SQL Databases, Data Streaming, Enterprise Data Management, Cloud Platform System, Information Technology, Data Analytics, Data Management, Data Delivery, Data Pipelines, Programming Languages
- **Published:** October 22, 2026
- **Apply:** https://transamerica.wd5.myworkdayjobs.com/US/job/Cedar-Rapids-Iowa/Sr-Data-Engineer_R20062679

## About the Role

* Bachelor's degree in computer science, math, engineering, or relevant technical field
 * Four years of collective experience in the application of data engineering, data analytics, data warehousing, business intelligence, database administration, and data integration concepts and methodologies
 * Three years of experience architecting, building, and administering big data and real-time streaming analytics architectures in on-premises and cloud environments
 * Two years of experience architecting, building, and administering large-scale distributed applications
 * Two years of experience with Linux operations and development, including basic commands and shell scripting
 * Two years of experience with execution of DevOps methodologies and continuous integration/continuous delivery
 * Expertise in SQL for data profiling, analysis, and extraction
 * Familiarity with data science techniques and frameworks
 * Creative thinker with strong analytical skills
 * Results oriented with a strong customer focus
 * Ability to work in a team environment
 * Strong technical communication skills
 * Ability to prioritize work to meet tight deadlines
 * Ability to learn and keep pace with the latest technology advances and quickly grasp new technologies to support the environment and contribute to project deliverables, * Master's degree in a technical field (e.g. computer science, math, engineering)
 * Solid understanding of big data and real time streaming analytics processing architecture and ecosystems
 * Practical experience with data warehousing architecture and implementation, including hands on experience with source to target mappings and developing ETL code
 * Experience with advanced analytics and machine learning concepts and technology implementations
 * Experience with data analysis and using data visualization tools to describe data
 * Relevant technology or platform certification (AWS, Microsoft, etc.)
 * Software development experience in relevant programming languages (i.e. Java, Python, Scala, Node.js)

## Description

The Senior Data Engineer is responsible for the design, architecture and support of systems, services and applications required for the collection, storage, processing, and analysis of all forms of data to enable data-driven decisions and outcomes across the enterprise., * Work collaboratively with other engineers, data scientists, analytics teams, and business product owners in an agile environment.

 * Architect, build, and support the operation of Cloud and On-Premises enterprise data infrastructure and tools.
 * Design robust, reusable, and scalable data driven solutions and data pipeline frameworks to automate the ingestion, processing and delivery of both structured and unstructured batch and real-time streaming data.
 * Build data APIs and data delivery services to support critical operational processes, analytical models and machine learning applications.
 * Assist in selection and integration of data related tools, frameworks, and applications required to expand platform capabilities.
 * Understand and implement best practices in management of enterprise data, including master data, reference data, metadata, data quality and lineage.
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