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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - US Hybrid - **Company:** Siemens AG - **Location:** State College, PA, United States (Remote available) - **Experience:** Expert - **Salary:** $109,800.0 - $197,700.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Computing Platforms, Microsoft Azure, Big Data, Software as a Service, Cloud Computing, Databases, Continuous Delivery, Continuous Integration, Data as a Services, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Extract Transform Load (ETL), Data Security, Data Vault Modeling, Data Warehousing, Relational Databases, Distributed Computing Environment, Fault Tolerance, Graph Database, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, SQL Azure, MongoDB, MySQL, Neo4j, NoSQL, Performance Tuning, Queueing Systems, SQL Stored Procedures, SQL Databases, Data Streaming, Data Processing, Google Cloud, Data Storage Technologies, Azure Data Factory, Apache Spark, Microsoft Fabric, Amazon Relational Database Service, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Cassandra, AWS Glue, Data Analytics, Star Schema, Real Time Data, Apache Kafka, Data Management, Machine Learning Operations, Terraform, Data Pipelines, Legacy Systems, Databricks, Programming Languages - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=07dcbc28785406a5 ## About the Role * At least Bachelors in Computer Science or equivalent * 6-8 years of hands-on experience in a dedicated Data Engineering role. * Expert-level proficiency in SQL and at least one high-level programming language, such as Python or Scala, used for data manipulation and engineering tasks. * Proven experience in designing and managing data platforms using a Lakehouse architecture (e.g., Databricks/Delta Lake, Apache Hudi, Apache Iceberg, or similar cloud-native lakehouse services). * Solid understanding of cloud platforms: Azure, AWS or GCP and their relevant data services (e.g., S3/ADLS/GCS for storage, Spark services) preferably Azure. * In-depth knowledge of database fundamentals, including schema design, performance tuning, and practical experience with both Relational and NoSQL databases. * Familiarity with distributed processing frameworks (e.g., Apache Spark) for handling large-scale data transformation. * Experience implementing and maintaining automated ETL/ELT data pipelines and utilizing data orchestration tools. * Strong understanding of data modeling techniques (e.g., Star Schema, Data Vault). * Familiarity with MLOps Preferred Qualifications * Experience with real-time streaming technologies (e.g., Apache Kafka, Kinesis, Pub/Sub). * Familiarity with Infrastructure as Code (IaC) tools like Terraform. * Experience in MLOps and serving production-ready data to ML systems. * Relevant professional cloud certification (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer, Microsoft Certified Azure Data Engineer). * Experience with graph database and familiarity with knowledge graphs and semantic processing NOTE: Applicants will not require employer sponsored work authorization now or in the future for employment in the USA. Applicants must be legally authorized for employment in the USA. ## Description Seeking a highly skilled and experienced Data Engineer to join our growing data team. The ideal candidate will be a technical specialist who is passionate about designing, building, and optimizing scalable, reliable, and high-performance data infrastructure. This role is crucial in architecting our next-generation data platform to unify data warehousing and data lake capabilities. You will be responsible for creating robust data pipelines, managing diverse database technologies, and ensuring high data quality for our Data Scientists, Analysts, and business stakeholders., Data Engineering & Architecture * Design, implement, and optimize the overall data architecture, with a strong focus on the Lakehouse paradigm (e.g., using Databricks/Delta Lake, Microsoft Fabric, or equivalent cloud-native solutions). * Develop and manage data models (dimensional, relational, or NoSQL) for both transactional and analytical systems, ensuring efficiency and scalability. * Successfully migrate or integrate data from legacy systems and disparate sources into the modern Lakehouse environment. * Monitor, tune, and optimize data storage, compute costs, and query performance across the data platform. Data Pipeline Development (ETL/ELT) * Design, build, and maintain robust, scalable, and fault-tolerant ETL/ELT data pipelines for batch and real-time data ingestion and transformation. * Integrate data from a variety of sources, including transactional databases, APIs, message queues (e.g., Kafka), and external SaaS platforms. * Implement data quality checks, validation rules, and data governance policies within the pipelines to ensure data reliability and compliance. * Use workflow orchestration tools (e.g., Apache Airflow, Azure Data Factory, AWS Glue) to automate and manage complex data workflows. Database Management * Demonstrate strong working knowledge of and hands-on experience with various database management systems (DBMS). * + Relational Databases (SQL): PostgreSQL, MySQL, SQL Server, or cloud-based relational services (e.g., AWS RDS, Azure SQL Database). + NoSQL Databases: Experience with one or more NoSQL types (e.g., Document-based like MongoDB/CosmosDB, Key-Value, Graph, or Columnar databases like Cassandra and Neo4J). * Optimize database schemas and write complex, efficient SQL queries and stored procedures for data manipulation and retrieval. Collaboration & Operations * Collaborate closely with Data Scientists and Data Analysts to deliver high-quality, feature-rich datasets that support advanced analytics and Machine Learning (ML) models. * Establish and maintain Continuous Integration/Continuous Deployment (CI/CD) practices for all data-related infrastructure and code. * Develop comprehensive technical documentation on data pipelines, data models, and platform architecture. * Ensure data security, access control, and compliance with data privacy regulations (e.g., GDPR, HIPAA). ## Related Videos - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [MySQL Protocol Features You Should Be Aware Of](https://www.wearedevelopers.com/videos/100267-mysql-protocol-features-you-should-be-aware-of) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)