Since 2012, we ve grown to become one of the leading single-family rental companies and homebuilders in the country, recently recognized as a top employer by Fortune and Great Place To Work®. At AMH, our goal is to simplify the experience of leasing a home through professional management and maintenance support, so our residents can focus on what really matters to them, wherever they are in life.
The Senior Data Engineer is responsible for designing, building, and managing the data platform and tools to allow for the efficient processing and analysis of large data sets. Develops and maintains scalable data pipelines, ensures data quality, and deploys machine learning models to production. Collaborates with business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization. Builds real-time and batch pipelines to handle large volumes of data efficiently. Collaborates with cross-functional teams and translate business requirements into scalable data solutions.
Responsibilities:
Design, develop, and maintain real-time or batch data pipelines to process and analyze large volumes of data. Designs and develops programs and tools to support ingestion, curation, and provisioning of complex first party and third-party data to achieve analytics, reporting, and data science. Design and develop Advanced Data Products and Intelligent API’s. Monitors the system performance by performing regular tests, troubleshoots, and integrates new features.
Lead in analysis of data and the design the data architecture to support BI, AI/ML and data products.
Designs and implements data platform architecture to meet organization analytical requirements. Ensures the solution designs address operational requirements such as scalability, maintainability, extensibility, flexibility, and integrity.
Provide technical leadership and mentorship to team members. Leads peer development and code reviews with focus on test driven development and Continuous Integration and Continuous Development (CICD).
Requirements:
Bachelor’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field required.
Master’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or 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 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, data processing, and analytical pipelines for big data, NoSQL, and data warehouse solutions.
Hands-on experience implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmo 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.
May occasionally work evenings and/or weekends.
Compensation
The anticipated pay range/scale for this position is $121,116.00 to $151,395.00 Annually. Actual starting base pay within this range will depend on factors including geographic location, education, training, skills, and relevant experience.
Additional Compensation
This position is eligible to receive a discretionary annual bonus.
Perks and Benefits
Employees have the opportunity to participate in medical, dental and vision insurance; flexible spending accounts and/or health savings accounts; dependent savings accounts; 401(k) with company matching contributions; employee stock purchase plan; and a tuition reimbursement program. The Company provides 9 paid holidays per year, and, upon hire, new employees will accrue paid time off (PTO) at a rate of 0.0577 hours of PTO per hour worked, up to a maximum of 120 hours per year.
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Requirements
Must-haves
Lead in analysis of data and the design the data architecture to support BI, AI/ML and data products.
Provide technical leadership and mentorship to team members. Leads peer development and code reviews with focus on test driven development and Continuous Integration and Continuous Development (CICD).
Bachelor’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field required.
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 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, data processing, and analytical pipelines for big data, NoSQL, and data warehouse solutions.
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.
May occasionally work evenings and/or weekends.
Nice-to-haves
Master’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field preferred.
Experience in ML and ML Pipeline a plus
Application prep
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