Lead Analyst, Data Operations
About The Position
The Lead Analyst, Data Operations leads the design, execution, and continuous improvement of enterprise-wide data operations processes supporting reliable, high-quality, accessible data for 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, and helps move manually maintained processes to automated, documented systems. It also manages data partner and vendor relationships, advances governance and international data expansion, promotes automation and AI tooling, and coaches junior and mid-level analysts without formal supervisory authority. Success is measured by the scalability, automation, and reliability of data operations, strong vendor and governance relationships, and elevated technical capability across the team.
Requirements
- Bachelor’s degree plus 3 years of related work experience, an advanced degree plus 1 year of related work experience, or an equivalent combination of education and experience.
- 7–10 years of experience identifying, querying, cleaning, wrangling, assessing the quality of, and managing data across relational and non-relational databases in big data environments, 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 support 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 for data integration, pipeline automation, billing, file transfer, and governance across on-premises and multi-cloud environments, including Azure, AWS, and Google Cloud.
- 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; and partner with Engineering, Platform, and external vendor teams to resolve root causes.
- Lead migration of manually maintained processes to automated, documented systems, eliminating single points of failure and enabling self-service for data refresh, reporting, and dashboards.
- 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 across partner integrations.
- Increase adoption of automation and AI tooling to reduce manual effort and create 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 team 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, depending on role and eligibility.
- 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, back-up 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 insurance.
- Mobile service and home internet discounts for eligible employees.
- Pet insurance for eligible employees.
- Commuter and transit programs for eligible employees.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
