Senior Data Engineer

American Homes 4 Rent - Las Vegas, NV

Full-time - Senior

Las Vegas, NV

Real Estate

About the position

The Senior Data Engineer at AMH is responsible for designing, building, and managing the data platform and tools necessary for efficient processing and analysis of large data sets. This role involves developing scalable data pipelines, ensuring data quality, and deploying machine learning models to production. The engineer collaborates with business teams to enhance data models that support business intelligence tools, thereby promoting data-driven decision-making across the organization.

Responsibilities

• Design, develop, and maintain real-time or batch data pipelines to process and analyze large volumes of data.
• Design and develop programs and tools to support ingestion, curation, and provisioning of first-party and third-party data for analytics, reporting, and data science.
• Design and develop Advanced Data Products and Intelligent APIs.
• Monitor system performance through regular tests, troubleshoot issues, and integrate new features.
• Lead analysis of data and design data architecture to support BI, AI/ML, and data products.
• Design and implement data platform architecture to meet organizational analytical requirements, ensuring scalability, maintainability, extensibility, flexibility, and integrity.
• Provide technical leadership and mentorship to team members, leading peer development and code reviews with a focus on test-driven development and CI/CD.

Requirements

• Bachelor's degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, or a related field required.
• Master's degree in a related field preferred.
• Minimum of eight (8) years of experience as a data engineer with full-stack capabilities.
• Minimum of ten (10) years of experience in programming.
• Minimum of five (5) years in Cloud technologies like Azure, AWS, or Google.
• Strong SQL knowledge.
• Experience in ML and ML Pipeline is a plus.
• Experience in real-time integration, developing intelligent apps and data products.
• Proficiency in Python and experience with CI/CD practices.
• Strong background in IAAS platforms and infrastructure.
• Hands-on experience with Databricks, Spark, Fabric, or similar technologies.
• Experience in Agile methodologies.
• Hands-on experience in the design and development of data pipelines and data products.
• Experience in developing data ingestion, processing, and analytical pipelines for big data, NoSQL, and data warehouse solutions.
• Hands-on experience implementing data migration and processing using Azure services: ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks, Azure Data Catalog, Cosmos DB, ML Studio, AI/ML, etc.
• Extensive experience in Big Data technologies such as Apache Spark and streaming technologies such as Kafka, EventHub, etc.
• Extensive experience in designing data applications in a cloud environment.
• Intermediate experience in RESTful APIs, messaging systems, and AWS or Microsoft Azure.
• Extensive experience in Data Architecture and data modeling.
• Expert in data analysis and data quality frameworks.
• Knowledgeable with BI tools such as Power BI and Tableau.
• Ability to work in a fast-paced, dynamic environment and manage multiple priorities effectively.
• Excellent communication and collaboration skills.
• Advanced understanding of data security best practices.
• Advanced understanding of systems and data integration architecture.
• Critical thinking and problem-solving skills, including root cause analysis and process improvement ability.
• Proven ability to perform high-quality technical documentation and presentations.
• Excellent organization, time management, and communication skills.

Nice-to-haves

• Experience in machine learning and machine learning pipelines.
• Knowledge of BI tools such as Power BI and Tableau.

Benefits

• People-first culture of trust, belonging, and inclusion.
• Opportunities for collaboration and initiative.