Senior Data Engineer

Homes 4 Rent

. Design, develop, and maintain real-time or batch data pipelines processing and analyzing large data volumes .

Posted 10/5/2026full-timeUnited StatesSenior💰 $121,116 - $151,395 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable data pipelines and architectures, with a strong focus on cloud technologies and data analysis. Proficient in leading technical teams and implementing machine learning models in production environments.

Highest-signal resume keywords

Data Pipeline DevelopmentCloud Technologies (Azure, AWS, Google Cloud)SQL ProficiencyPython ProgrammingData Architecture Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringMachine Learning PipelinesData IngestionData ProcessingBig Data TechnologiesData ModelingRESTful APIsCI/CD PracticesAgile MethodologiesData Quality Frameworks

Soft Skills

Technical LeadershipMentorshipCollaborationProblem-SolvingCommunication

Tools & Technologies

DatabricksApache SparkAzure Data FactoryEvent HubIoT HubAzure Stream AnalyticsPower BITableauCosmos DBML Studio

Certifications & Qualifications

Bachelor’s Degree in Computer Science or Related FieldMaster’s Degree in Related Field (Preferred)

Industry Keywords

Business IntelligenceData ProductsReal-Time IntegrationData Warehouse SolutionsStreaming Technologies

Tech Stack

Tools & technologies

ApacheAWSAzureCloudIoTKafkaNoSQLPythonSparkSQLTableau

About the role

Key responsibilities & impact

Design, develop, and maintain real-time or batch data pipelines processing and analyzing large data volumes
Develop programs and tools for ingestion, curation, and provisioning of complex first-party and third-party data
Design and develop advanced data products and intelligent APIs
Monitor system performance through regular testing, troubleshooting, and feature integration
Lead data analysis and data architecture design supporting BI, AI/ML, and data products
Design and implement data platform architecture meeting analytical requirements
Ensure solution designs address scalability, maintainability, extensibility, flexibility, and integrity
Provide technical leadership and mentorship to team members
Lead peer development and code reviews focused on test-driven development and CI/CD
Collaborate with business and cross-functional teams to translate requirements into scalable data solutions
Improve data models supporting business intelligence tools and data-driven decision-making
Deploy machine learning models to production

Requirements

What you’ll need

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 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 such as Azure, AWS, or Google Cloud
Strong SQL knowledge
Experience in ML and ML pipelines 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 designing and developing data pipelines and data products
Experience 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, including ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmos DB, ML Studio, and AI/ML
Extensive experience with big data technologies such as Apache Spark and streaming technologies such as Kafka and EventHub
Extensive experience designing data applications in a cloud environment
Intermediate experience with 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
Knowledge of BI tools such as Power BI and Tableau
May occasionally work evenings and/or weekends

Benefits

Comp & perks

Discretionary annual bonus
Medical insurance
Dental insurance
Vision insurance
Flexible spending accounts
Health savings accounts
Dependent savings accounts
401(k) with company matching contributions
Employee stock purchase plan
Tuition reimbursement program
9 paid holidays per year
Paid time off (PTO), accrued at 0.0577 hours per hour worked, up to 120 hours per year