Lead Analyst, Data Operations

T-Mobile USA•New York, NY

About The Position

The Lead Analyst, Data Operations leads the design, execution, and continuous improvement of enterprise-wide data operations processes that ensure the reliability, quality, and accessibility of data supporting T-Ads business decisions. The role is the senior technical authority for data integrations, pipeline automation, and governance across on-premises and multi-cloud environments, partnering with Engineering, Platform, and external vendor teams to resolve complex, high-impact issues. The position owns end-to-end data operations frameworks, service-level standards, and escalation processes. It also coaches and mentors junior and mid-level data analysts without formal supervisory authority. Success is measured by the scalability, automation, and reliability of data operations, strong vendor and governance relationships, and the ability to elevate technical capability across the team. The work enables T-Ads to scale data-driven advertising decisions with speed, accuracy, and trust.

Requirements

Bachelor’s degree plus 3 years of related work experience, or an advanced degree with 1 year of related work experience, or an equivalent combination of education and experience.
7–10 years of experience in data identification, querying, cleaning, wrangling, quality assessment, and management across relational and non-relational databases in big data environments, both on-premises and in cloud environments such as Azure, AWS, and Google Cloud.
7–10 years of experience translating complex business questions into data strategy and applying advanced statistical and analytical techniques to drive enterprise-level decisions.
7–10 years of experience communicating technical concepts to executive, technical, and lay audiences, including data-driven presentations to senior stakeholders.
7–10 years of experience working with relational databases using SQL.
7–10 years of experience with data visualization tools such as Power BI or Tableau.
4–7 years of experience with big data architecture and pipelines, such as Hadoop, Hive, Spark, and Kafka.
4–7 years of experience with enterprise data integration, ETL/ELT automation, and cloud-based data platforms such as Snowflake, dbt, or Airflow.
3–5 years of experience managing or coordinating vendor and data partner relationships, including SLA and contract performance oversight.
2–4 years of experience coaching or mentoring junior analysts or team members on data analysis and quality best practices.
At least 18 years of age.
Legally authorized to work in the United States.

Nice To Haves

3–5 years of experience with API-driven data integration, including REST APIs and GraphQL.
2–4 years of experience contributing to data governance frameworks, policies, and compliance or audit readiness.

Responsibilities

Own and continuously improve enterprise data operations frameworks, service-level standards, and escalation processes covering data integration, pipeline automation, billing, file transfer, and governance across on-premises and multi-cloud environments.
Serve as the senior technical authority and escalation point for complex data quality, integration, and pipeline issues; build and maintain infrastructure using tools including Snowflake, AWS Lambda, S3, and Streamlit.
Partner with Engineering, Platform, and external vendor teams to drive root-cause resolution of complex issues.
Lead migration of manually maintained processes to fully automated, documented systems, eliminating single points of failure and enabling self-service data refresh, reporting, and dashboard processes.
Manage data partner and vendor relationships, ensuring adherence to SLAs, contract terms, and performance standards for data tools and platforms.
Drive data governance standards and international data expansion efforts across partner integrations.
Increase adoption of automation and AI tooling to reduce manual effort and free capacity for higher-leverage technical work.
Coach and mentor junior and mid-level data analysts on advanced data analysis, quality, and tooling best practices, elevating technical capability and data literacy without formal supervisory authority.
Perform other duties and projects as assigned by business management.

Benefits

Competitive base salary and compensation package.
Annual stock grant and employee stock purchase plan.
401(k) and access to free, year-round money coaches.
Annual bonus or periodic sales incentive or bonus for eligible employees.
Medical, dental, and vision insurance.
Flexible spending account.
Paid time off and up to 12 paid holidays.
Paid parental and family leave.
Family-building benefits, backup care, enhanced family support, and childcare subsidy.
Tuition assistance and college coaching.
Short- and long-term disability coverage.
Voluntary AD&D, accident, life, disability, and long-term care coverage.
Mobile service and home internet discounts for eligible employees.
Pet insurance for eligible employees.
Commuter and transit programs for eligible employees.