Senior Technical Program Manager

Internet Brands•El Segundo, CA

36d•$100,000

About The Position

We are looking for a Senior Technical Program Manager to join our Technology Organization, aligned with our Data Engineering function across the Legal vertical. This is a hands-on execution role coordinating across Data Engineering, Product Engineering, BI/Analytics, System Engineering, and NOC — where shared infrastructure, legacy systems, and evolving platforms create complex, interdependent delivery challenges. The ideal candidate is a strong self-starter who navigates ambiguity, builds cross-functional relationships, and drives business-critical initiatives with sound judgment on both immediate and long-term trade-offs. The program portfolio spans large-scale data platform migrations, ETL/ELT pipeline development, BI reporting migrations, and data architecture modernization across legacy and modern platforms — including programs where a single infrastructure change creates cascading dependencies across multiple downstream product teams. Lead strategic program planning and execution – driving discovery, prioritization, milestone development, dependency management, and risk mitigation in close collaboration with product and engineering leads; communicate progress, risks, and retrospectives consistently across all stakeholder levels Manage programs where shared data infrastructure serves as a dependency for multiple concurrently executing product teams – maintaining alignment across competing consumer priorities while the underlying platform is actively evolving Define and track measurable success criteria for data platform programs, including pipeline SLA targets, consumer team readiness gates, data quality acceptance benchmarks, and migration sign-off standards Proactively identify and remove impediments, lead issue resolution, and support teams balancing competing priorities Partner with stakeholders, product managers, and engineering to translate requirements into technical execution plans, and collaborate on solution architecture from design through deployment and adoption Ensure continuity of systems and data flows through migrations, upgrades, and platform changes – coordinating across data, application, and infrastructure layers to protect downstream consumers and production environments Lead end-to-end planning of large-scale data platform migrations – from legacy big data clusters (e.g., Hadoop/Cloudera) to modern platforms – including migration roadmap definition, API/query/table dependency mapping, phased cutover sequencing, and multi-workstream coordination across consuming teams Drive data quality and validation strategies for production migrations, including pre/post-migration validation frameworks, rollback plans, and sign-off criteria; track and communicate platform health, SLA adherence, and risk posture to engineering leadership Manage complex multi-phase infrastructure upgrade programs including platform version upgrades, cluster expansions, and compute environment migrations Facilitate alignment between data engineering teams and downstream consumers (application teams, analytics, BI, marketing operations) to ensure pipeline continuity through platform transitions Support data governance and lineage documentation efforts to improve discoverability, quality, and reliability of data assets across the organization

Requirements

8+ years of TPM experience in a scaled technology organization, with a track record of managing concurrent programs spanning multiple engineering teams, product lines, and organizational boundaries simultaneously
Background in product-driven SaaS or subscription businesses where data infrastructure directly supports revenue-generating product lines
Demonstrated ability to manage programs with significant discovered scope – where initial estimates expand as dependency mapping uncovers technical complexity across multiple consuming teams
Strong stakeholder management skills in shared-infrastructure contexts, where multiple product teams have competing timelines and priorities against the same platform dependencies
Comfortable building and adapting program management workflows using low-code/no-code platforms (e.g., Airtable) – including project tracking, reporting templates, and cross-team dashboards
BS/BA degree required, preferably in computer science or technical disciplines
3+ years managing data engineering programs – with demonstrated experience planning and executing complex, multi-phase data migrations including scope definition, dependency mapping, phased cutover, validation, and post-migration stabilization
Strong understanding of distributed systems and modern data architectures (data lakes, warehouses, pipelines); familiarity with big data infrastructure such as Hadoop/Cloudera, Impala, Spark, or Postgres
Experience managing cross-team dependencies between data engineering and application teams against shared APIs, tables, and pipelines; ability to engage technically with data engineers on schema design, data lineage, table partitioning, and query migration without writing code
Understanding of BI tooling (Tableau, Power BI, Looker) and how reporting layers depend on underlying data pipeline health
Experience managing platform version upgrades, cluster transitions, or infrastructure modernization at scale

Nice To Haves

Scrum Master, Scaled Agilist, or PMP Certification
Experience owning end-to-end program strategy and communicating results to senior leadership
Track record of maintaining alignment and momentum on long-horizon programs (12+ months) where scope, priorities, and resources regularly shift – including programs where a single shared infrastructure dependency creates cascading timeline impact across multiple downstream teams
Familiarity with modern analytical data platforms (Snowflake, Apache Doris, Vertica) and data orchestration/transformation tooling (dbt, Apache Airflow, Informatica, Pentaho)
Experience with cloud-based data platforms (AWS, GCP, Azure) spanning both cloud and on-premises infrastructure
Experience managing data governance, data quality, or compliance programs (GDPR, CCPA)
Exposure to machine learning or predictive modeling programs from a TPM perspective (e.g., ML pipelines, model scoring, AI-powered analytics)

Responsibilities

Lead strategic program planning and execution – driving discovery, prioritization, milestone development, dependency management, and risk mitigation in close collaboration with product and engineering leads; communicate progress, risks, and retrospectives consistently across all stakeholder levels
Manage programs where shared data infrastructure serves as a dependency for multiple concurrently executing product teams – maintaining alignment across competing consumer priorities while the underlying platform is actively evolving
Define and track measurable success criteria for data platform programs, including pipeline SLA targets, consumer team readiness gates, data quality acceptance benchmarks, and migration sign-off standards
Proactively identify and remove impediments, lead issue resolution, and support teams balancing competing priorities
Partner with stakeholders, product managers, and engineering to translate requirements into technical execution plans, and collaborate on solution architecture from design through deployment and adoption
Ensure continuity of systems and data flows through migrations, upgrades, and platform changes – coordinating across data, application, and infrastructure layers to protect downstream consumers and production environments
Lead end-to-end planning of large-scale data platform migrations – from legacy big data clusters (e.g., Hadoop/Cloudera) to modern platforms – including migration roadmap definition, API/query/table dependency mapping, phased cutover sequencing, and multi-workstream coordination across consuming teams
Drive data quality and validation strategies for production migrations, including pre/post-migration validation frameworks, rollback plans, and sign-off criteria; track and communicate platform health, SLA adherence, and risk posture to engineering leadership
Manage complex multi-phase infrastructure upgrade programs including platform version upgrades, cluster expansions, and compute environment migrations
Facilitate alignment between data engineering teams and downstream consumers (application teams, analytics, BI, marketing operations) to ensure pipeline continuity through platform transitions
Support data governance and lineage documentation efforts to improve discoverability, quality, and reliability of data assets across the organization

Benefits

health insurance options such as medical, dental, and vision coverage
flexible spending accounts (FSA) for medical and dependent care
short-term and long-term disability insurance
life and AD&D insurance
401(k) retirement savings plan with a company match
paid time off (PTO)
paid holidays
commuter benefits
access to our Employee Assistance Program (EAP) and well-being coaching services
voluntary benefits such as home, auto and pet insurance, and discounted legal and financial services