Senior Software Engineer II, Ads Data Solutions Engineering

• 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. • 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). Why this role is a great opportunity.... • 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 cro

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Ads DSE team builds the core capabilities that power Instacart's off-platform advertising, secure data collaboration (cleanrooms), automated taxonomy management, and their associated platform foundations. We are hiring a Senior Engineer II (L6) to co-own the technical roadmap, modernize our data solutions infrastructure, scale off-platform integrations and measurement capabilities, extend our cleanroom collaboration capabilities, and automate taxonomy change management workflows. This role is pivotal for cross-team collaboration, developer productivity, and AI-driven development initiatives. You are a senior technical leader who designs and ships scalable, data‑intensive systems; drives cross‑team execution; and raises engineering standards. You’ll partner closely with Product, Data Science, Data Platform, and Governance teams to build reusable abstractions and deliver high‑impact features across our pillars: Off‑platform, Data collaboration (cleanrooms), Ads Taxonomy, Platform, and New Initiatives (AI). You will mentor L4/L5 engineers, act as an IC tech lead (no direct reports), and help define a future on‑call model and SLOs. 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. • 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. • 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). About You 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