Instacart
Senior Software Engineer II, Ads Data Solutions Engineering
Rol remoto de Software Engineering con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Canadá
Resumen del rol
Senior Software Engineer II, Ads Data Solutions Engineering
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
About the Job
- Technical leadership and roadmap
- Lead architecture for reusable, scalable systems across off‑platform workflows, cleanrooms, taxonomy automation, and the Ads Data Solutions Platform.
- Evolve core abstractions, testing, CI/CD, observability, and cost efficiency; proactively drive modernization.
- Propose and drive initiatives on behalf of engineering management; align stakeholders and manage dependencies.
Details
- Lead architecture for reusable, scalable systems across off‑platform workflows, cleanrooms, taxonomy automation, and the Ads Data Solutions Platform.
- Evolve core abstractions, testing, CI/CD, observability, and cost efficiency; proactively drive modernization.
- Propose and drive initiatives on behalf of engineering management; align stakeholders and manage dependencies.
- Off‑platform: expand and harden integrations with external advertising platforms; design privacy-forward activation and identity workflows; reduce reliance on third-party intermediaries; and build measurement ingestion pipelines for performance signals such as reach, frequency, and conversions.
- Data collaboration (cleanrooms): extend our cleanroom orchestration and governance tooling (multi-cleanroom support, policy enforcement), develop reusable query templates and partner configurations, optimize pipelines for cost and performance, and scale secure data collaboration deployment and management.
- Ads Taxonomy: lead intake automation (UI + backend) and release workflow improvements to reduce manual effort and cycle time.
- Platform: assist with platform modernization and developer tooling improvements; contribute to an on‑call/SLO strategy as we mature operations.
- Use AI‑assisted tools daily for design, coding, tests, and docs; define team prompt patterns and workflows; identify AI opportunities in internal tools and ops.
- Translate ambiguous requirements into pragmatic phases (POC, pilot, production) with clear SLAs/SLOs.
- Champion security‑by‑design, data governance, and privacy compliance (e.g., GDPR/CCPA) across pipelines.
- Mentor engineers up to L5; set code quality and review standards.
- Build cross‑team partnerships (Ads Manager, Measurement Science, Data Platform, Privacy/Legal, and external platforms).
- 8+ years of software engineering experience (typically 10+ for this level) delivering and operating large‑scale backend/data systems; led cross‑team projects and architectural decisions.
- Strong in Python and one of Ruby or Go; services/APIs (REST/gRPC); integrations with third‑party APIs (e.g., Meta, Google, The Trade Desk).
- Data pipelines with DBT and Airflow; Spark/Databricks; advanced SQL and performance tuning.
- Snowflake and AWS experience; cost‑aware design; workflow orchestration (e.g., Temporal) and event‑driven patterns.
- Experience with ad‑tech/programmatic and measurement integrations; cleanrooms (Snowflake DCR, shares/listings); identity/matching (UID2, RampID) and deconfliction.
- Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows.
- CI/CD, containers, test strategy; observability (metrics/logs/tracing) with tools like Datadog; incident readiness and SLO thinking.
- Demonstrated, recent hands-on use of AI‑assisted development tools (e.g., GitHub Copilot, Cursor, OpenAI‑based assistants) to improve speed and quality.
- Experience defining reusable prompts/workflows for team use and contributing to AI‑enabled internal tools or automation.
- Ability to evaluate when to apply AI vs. deterministic systems; familiarity with evaluation, guardrails, and security/privacy implications in AI usage.
- Clear technical writing; stakeholder management; ability to drive consensus and unblock execution.
About the Job
- Pillar execution
- Off‑platform: expand and harden integrations with external advertising platforms; design privacy-forward activation and identity workflows; reduce reliance on third-party intermediaries; and build measurement ingestion pipelines for performance signals such as reach, frequency, and conversions.
- Data collaboration (cleanrooms): extend our cleanroom orchestration and governance tooling (multi-cleanroom support, policy enforcement), develop reusable query templates and partner configurations, optimize pipelines for cost and performance, and scale secure data collaboration deployment and management.
- Ads Taxonomy: lead intake automation (UI + backend) and release workflow improvements to reduce manual effort and cycle time.
- Platform: assist with platform modernization and developer tooling improvements; contribute to an on‑call/SLO strategy as we mature operations.
- AI‑first engineering
- Use AI‑assisted tools daily for design, coding, tests, and docs; define team prompt patterns and workflows; identify AI opportunities in internal tools and ops.
- Product quality, privacy, and security
- Translate ambiguous requirements into pragmatic phases (POC, pilot, production) with clear SLAs/SLOs.
- Champion security‑by‑design, data governance, and privacy compliance (e.g., GDPR/CCPA) across pipelines.
About the Job
- Mentorship and collaboration
- Mentor engineers up to L5; set code quality and review standards.
- Build cross‑team partnerships (Ads Manager, Measurement Science, Data Platform, Privacy/Legal, and external platforms).
Minimum Qualifications
- Proven senior‑level impact
- 8+ years of software engineering experience (typically 10+ for this level) delivering and operating large‑scale backend/data systems; led cross‑team projects and architectural decisions.
- Backend and data engineering
- Strong in Python and one of Ruby or Go; services/APIs (REST/gRPC); integrations with third‑party APIs (e.g., Meta, Google, The Trade Desk).
- Data pipelines with DBT and Airflow; Spark/Databricks; advanced SQL and performance tuning.
- Snowflake and AWS experience; cost‑aware design; workflow orchestration (e.g., Temporal) and event‑driven patterns.
- Ads/cleanrooms/privacy
- Experience with ad‑tech/programmatic and measurement integrations; cleanrooms (Snowflake DCR, shares/listings); identity/matching (UID2, RampID) and deconfliction.
- Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows.
- Platform excellence
- CI/CD, containers, test strategy; observability (metrics/logs/tracing) with tools like Datadog; incident readiness and SLO thinking.
- AI fluency (must‑have)
- Demonstrated, recent hands-on use of AI‑assisted development tools (e.g., GitHub Copilot, Cursor, OpenAI‑based assistants) to improve speed and quality.
- Experience defining reusable prompts/workflows for team use and contributing to AI‑enabled internal tools or automation.
- Ability to evaluate when to apply AI vs. deterministic systems; familiarity with evaluation, guardrails, and security/privacy implications in AI usage.
- Collaboration and communication
- Clear technical writing; stakeholder management; ability to drive consensus and unblock execution.
Preferred Qualifications
- Direct experience with UID2/TTD integrations, Roku/Pubmatic/NBCU, or Meta Advanced Analytics/Google ADH pipelines.
- Catalog/taxonomy, entity lineage, or custom hierarchy systems.
- Snowflake governance patterns, partner data collaboration at scale.
- Vendor/partner management and external API certification programs.
- Building AI‑powered internal tools (e.g., Slackbots, data assistants).
Preferred Qualifications
- Lead foundational, high‑visibility initiatives and translate them into measurable impact on revenue, efficiency, and partner adoption.
- Co‑own the technical roadmap with scope to define abstractions, standards, and AI‑first workflows across multiple pillars.
- Ship impactful features end‑to‑end: direct UID2 activation, Share Manager extensions, taxonomy intake automation, and platform modernization.
- Collaborate with strong cross‑functional partners and enjoy occasional trips to our Toronto office to connect with the broader engineering community.
- Help define our future on‑call model and operational excellence standards as we scale.
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