Senior Software Engineer II, Ads Data Solutions Engineering
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
- 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 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.