Sr Engineers, Data

T-Mobile•Atlanta, GA

2d•$152,131 - $160,000•Hybrid

About The Position

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees! T-Mobile is America’s supercharged Un-carrier, delivering an advanced 4G LTE and transformative nationwide 5G network that will offer reliable connectivity for all. Senior Engineers, Data located in Atlanta, GA will develop data engineering solutions, including data pipelines, visualization, and analytical tools. Telecommuting is permitted, but applicants must live within a reasonable commuting distance. No additional national or international travel is anticipated.

Requirements

Designing and developing cloud-based data engineering solutions to ingest, process, and deliver large-scale structured and semistructured data for enterprise analytics, operational reporting, and feeds for downstream applications, enabling downstream analytics and operational reporting use cases, including supply chain analytics, inventory reporting, planning, and order fulfillment;
Applying SQL, relational modeling, and database development to build curated datasets, dimensional models, and governed reporting layers used for business intelligence, device sales reporting, product analytics, and operational dashboards;
Building streaming pipelines to ingest near real-time transformation and enrichment of event data (including clickstream, application logs, telemetry, or transactional events) and performing filtering, aggregation, and incremental computations, delivering low-latency datasets for operational dashboards, anomaly detection inputs, and time-sensitive analytics;
Diagnosing issues across ingestion, transformation, and serving layers using pipeline logs, query plans, reconciliation checks, and data quality validations. Using data engineering technologies (including ETL/ELT frameworks, orchestration tools, SQL engines, distributed processing, and reporting/BI platforms) to address challenges such as improving end-to-end visibility for order-to-delivery and shipment tracking and reducing stockouts/overstock by improving inventory accuracy and timeliness;
Applying AI/ML tools and frameworks to supply chain use cases that improve planning effectiveness, operational execution, and exception handling. Using managed AI/ML platforms to support AI/ML workflows including experimentation, evaluation, and deployment such as demand signal enhancement, lead time estimation, ETA prediction inputs, anomaly detection in inventory/shipment patterns, and prioritization of operational exceptions.

Responsibilities

Design and develop data architectures in on-premises, cloud and hybrid platforms.
Perform data wrangling of heterogeneous data, exploration and discovery in pursuit of new business insights.
Actively contribute to the team’s knowledge and drive new capabilities forward.
Mentor other team members in their efforts to build data engineering skillsets.
Assist team management in defining projects, including helping estimate, plan and scope work.
Prepare and contribute to presentations required by management.
Participate in architecture and design of various software and Data warehousing components focused on creating applications that leverage technologies such as virtualization using Denodo, Cloud platforms Azure Data Factory, Azure Databricks and Snowflake Data platforms and technologies.
Analyze code coverage using industry standard tools such as GitLab, GitGaurdian and Jenkins, ensure automated tests are integrated into the Continuous Delivery Pipeline, and design, develop, and maintain automation systems and tools to be used by development and test engineers.
Apply knowledge and experience in ETL Validation using SQL queries, as well as knowledge and experience on Database Management Tools and cloud technologies (e.g.: Microsoft SQL Server, Teradata, Oracle, Snowflake, Azure, Databricks).
Act as a liaison with the end-to-end test execution team, write and execute automated and manual tests to provide an ongoing measure of the quality of the product, and apply Automation tool experience.
Analyze code coverage using industry standard tools such as GitLab, GitGaurdian and Jenkins, ensure automated tests are integrated into the Continuous Delivery Pipeline, and design, develop, and maintain automation systems and tools to be used by development and test engineers.
Develop and integrate Agentic AI systems that autonomously orchestrate data workflows, perform contextual reasoning, and trigger downstream analytics or reporting actions.
Collaborate with cross-functional teams to identify opportunities to embed AI agents in data governance, metadata curation, and business process automation.