Job description

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it s our responsibility to put the planet first. For us at Trane Technologies , and through our businesses including Trane® and Thermo King , sustainability is not just how we do business—it is our business. Do you dare to look at the world s challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what s possible for a sustainable world. Learn about our benefits designed for you to Thrive at work and at home. We boldly go. Where is the work: Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires. We are looking for a Data Developer with deep, hands-on Azure data expertise to own and evolve the data foundation of our enterprise telematics SaaS platform. Our platform manages approximately 200,000 connected transport refrigeration units (TRUs) generating millions of telemetry events per day — alarms, sensor readings, engine state, geolocation, and operational metrics — flowing through a cloud-native IoT pipeline built on Azure. You will be responsible for the full data lifecycle: high-throughput ingestion from IoT devices, transformation and enrichment, storage strategy across Cosmos DB and Azure Data Explorer, relational data modeling in Azure SQL, analytics delivery, and pipeline reliability. This is a hands-on, high-impact role with direct influence over platform architecture, working closely with backend engineering, architecture, product, and leadership. You must be able to operate independently, take full ownership of the data platform, and bring proven experience building scalable, reliable, cost-optimized data solutions on Azure. Key Responsibilities Data Platform Architecture & Development Own the design and evolution of the platform s end-to-end data architecture across Cosmos DB , Azure Data Explorer (ADX) , Azure SQL, and Fabric . Architect and optimize Cosmos DB for high-throughput IoT workloads: partition key strategy, indexing policy, schema design, TTL configuration, RU/s throughput tuning, and change feed utilization. Build and manage ADX clusters: ingestion pipelines (Event Hub ingestion, ingestion mappings, update policies), KQL query optimization, retention and caching policy tuning, and materialized views for analytics. Design and manage Azure SQL schemas, stored procedures, and ETL jobs supporting relational reporting and operational data needs. Architect data flow across the hot path (Event Hubs → real-time processing), warm path (Cosmos DB operational queries), and cold/analytics path (ADX long-term telemetry retention and aggregation). Build and maintain ingestion pipelines using Azure Functions , Event Hubs , and Service Bus . ETL / ELT & Data Transformation Design and implement high-throughput ingestion pipelines processing millions of IoT device events per day, including telemetry, alarms, lifecycle events, and geospatial data. Build transformation and enrichment logic in C#/.NET, Python, and/or pySpark integrated with Azure Functions and Event Hub triggered pipelines. Implement data quality, validation, deduplication, and anomaly detection within ingestion pipelines. Apply CI/CD practices for data pipeline deployment using GitHub Actions or Azure DevOps . Design and maintain ADX update policies and Cosmos DB change feed processors for downstream data propagation. Data Modeling & Storage Strategy Design scalable, queryable data models for time-series telemetry, alarm events, geospatial lookups (H3 hexagonal indexing), and fleet/asset metadata. Implement optimal partitioning strategies tailored to Cosmos DB (tenant device key patterns) and ADX (ingestion time partitioning, row ordering policies). Model multi-tenant data isolation and access patterns in both Cosmos DB and Azure SQL. Manage data lifecycle policies across ADX (hot/cold cache tiers, retention) and Cosmos DB (TTL, archival strategy). Collaborate with backend engineering to define microservice data contracts and Cosmos DB document schemas that support both operational APIs and analytics queries. Cross-Functional Collaboration Partner with platform architects on the evolution of the next-generation telematics platform data architecture. Work closely with backend (JAVA) engineers to support ingestion patterns, event processing, and data contract design across microservices. Support product and business stakeholders with analytics queries, reporting, and ad hoc data investigation using ADX/KQL. Partner with project managers to deliver data milestones predictably and communicate risks early. Operations & Reliability Own reliability, observability, and SLA of all data pipelines across the production SaaS platform. Monitor, diagnose, and optimize costs across Cosmos DB (RU/s utilization), ADX (compute and storage tiers), Azure SQL, Event Hubs, and Azure Functions. Implement proper governance, RBAC, and data access controls consistent with multi-tenant SaaS requirements. Produce runbooks, architecture documentation, and knowledge-sharing artifacts for the engineering organization. Required Qualifications 5 years of professional data engineering experience with a track record of building and owning production data platforms. Education: Bachelor’s degree in Computer Science, Mathematics, Information Technology, or a related field. Deep, hands-on Azure data expertise , specifically: Cosmos DB (required) — partition strategy, indexing, change feed, TTL, multi-tenant patterns, RU optimization Azure Data Explorer (ADX) (required) — cluster management, ingestion pipelines, KQL, update policies, retention, caching tiers Azure SQL (required) — schema design, stored procedures, query optimization, ETL integration Azure Event Hubs and Service Bus — high-throughput ingestion, consumer group management, dead-letter handling Azure Functions — event-driven pipeline orchestration Microsoft Fabric -- Experience with Microsoft Fabric (Real-Time Analytics, Lakehouse, or Eventstream). Familiarity with Microsoft Fabric solutions, including Lakehouse architecture, data pipelines, and notebook-based transformations for scalable data engineering, analytics, and unified data workflows. Strong proficiency in KQL for ADX and SQL for Azure SQL; working proficiency in Python, pySpark and/or C#/.NET/JAVA/etc. for pipeline development. Solid understanding of multi-tenant SaaS data architecture — isolation patterns, shared infrastructure cost management, tenant-aware querying. Experience designing data models for time-series, telemetry, and event-driven workloads at scale. Strong understanding of distributed data systems — partitioning, consistency tradeoffs, throughput vs. latency optimization. Hands-on experience supporting and owning production SaaS platforms end-to-end. Knowledge and expertise in using Git for distributed version control, ability to resolve merge conflicts, knowledge of Git branching strategies. Knowledge and expertise in Azure DevOps deployment pipelines Experience in utilizing AI in a data platform ecosystem. Ability to operate independently and cross-functionally across architecture, development, DevOps, and product teams. Preferred / Nice-to-Have Experience in IoT, telematics, fleet management , or large-scale connected device platforms. Familiarity with geospatial data — H3 indexing, geofencing, or location-enriched telemetry pipelines. Familiarity with .NET / C# / JAVA in the context of Azure data pipeline development (Azure Functions, Event Hub processors). Experience with Azure Container Apps or other containerized Azure compute environments. Exposure to MQTT , IoT Hub , or cellular device connectivity (private APN) patterns. Annual Base Salary Range or Hourly Base Pay Range: $127,110.00 - $177,870.00 Compensation Type: Salary Incentive Eligible: Yes Sales Commission Eligible: No Disclaimer : We strive to provide competitive compensation for this position, tailored to a variety of factors. The actual compensation will depend on elements such as seniority, merit, geographic location, education, experience, travel requirements, and union designation. Our compensation range is generally based on the national average for the country. Additionally, benefits may vary depending on the region, business alignment, union involvement, and employee status. Thrive at work and at home: Benefits kick in on DAY ONE for you and your family, including health insurance and holistic wellness programs that include generous incentives – WE DARE TO CARE! Family building benefits include fertility coverage and adoption/surrogacy assistance. Paid time off includes up to 15 vacation days, paid holidays, sick leave, and additional options to support volunteer and parental leave. 401K match up, educational and training opportunities through company programs along with tuition assistance and student debt support. Disclaimer: Benefit offerings may vary by site as well as Collective Bargaining Agreements and local/state regulations Safety Sensitive Role: No The company designates certain roles as Safety Sensitive. Safety Sensitive roles may require that you pass additional drug screening. We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.

Requirements

Must-haves

Learn about our benefits designed for you to Thrive at work and at home.
We boldly go.
Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires.
You must be able to operate independently, take full ownership of the data platform, and bring proven experience building scalable, reliable, cost-optimized data solutions on Azure.
Data Platform Architecture & Development
Own the design and evolution of the platform s end-to-end data architecture across Cosmos DB , Azure Data Explorer (ADX) , Azure SQL, and Fabric .
Architect and optimize Cosmos DB for high-throughput IoT workloads: partition key strategy, indexing policy, schema design, TTL configuration, RU/s throughput tuning, and change feed utilization.
Build and manage ADX clusters: ingestion pipelines (Event Hub ingestion, ingestion mappings, update policies), KQL query optimization, retention and caching policy tuning, and materialized views for analytics.
Design and manage Azure SQL schemas, stored procedures, and ETL jobs supporting relational reporting and operational data needs.
Architect data flow across the hot path (Event Hubs → real-time processing), warm path (Cosmos DB operational queries), and cold/analytics path (ADX long-term telemetry retention and aggregation).
Build and maintain ingestion pipelines using Azure Functions , Event Hubs , and Service Bus .
ETL / ELT & Data Transformation
Design and implement high-throughput ingestion pipelines processing millions of IoT device events per day, including telemetry, alarms, lifecycle events, and geospatial data.
Build transformation and enrichment logic in C#/.NET, Python, and/or pySpark integrated with Azure Functions and Event Hub triggered pipelines.
Implement data quality, validation, deduplication, and anomaly detection within ingestion pipelines.
Apply CI/CD practices for data pipeline deployment using GitHub Actions or Azure DevOps .
Design and maintain ADX update policies and Cosmos DB change feed processors for downstream data propagation.
Data Modeling & Storage Strategy
Design scalable, queryable data models for time-series telemetry, alarm events, geospatial lookups (H3 hexagonal indexing), and fleet/asset metadata.
Implement optimal partitioning strategies tailored to Cosmos DB (tenant device key patterns) and ADX (ingestion time partitioning, row ordering policies).
Model multi-tenant data isolation and access patterns in both Cosmos DB and Azure SQL.
Manage data lifecycle policies across ADX (hot/cold cache tiers, retention) and Cosmos DB (TTL, archival strategy).
Collaborate with backend engineering to define microservice data contracts and Cosmos DB document schemas that support both operational APIs and analytics queries.

Nice-to-haves

Preferred / Nice-to-Have

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

goazuresqlpythonci/cdjavaai

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Health Insurance

401k

Paid Time Off

Parental Leave

Wellness