Senior Software Engineer II, Ads Data Solutions Engineering
Instacart
Senior Software Engineer II, Ads Data Solutions Engineering
Job Description
Responsibilities
- 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).
Required Qualifications
- 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.
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).
Required Skills
- Python
- Ruby or Go
- REST/gRPC
- Third-party APIs (Meta, Google, The Trade Desk)
- DBT
- Airflow
- Spark/Databricks
- Advanced SQL
- Snowflake
- AWS
- Temporal
- Event-driven patterns
- Ad-tech/programmatic
- Cleanrooms (Snowflake DCR)
- UID2, RampID
- GDPR/CCPA
- CI/CD
- Containers
- Datadog
- GitHub Copilot
- Cursor
- OpenAI-based assistants
Benefits
- Highly market-competitive compensation
- New hire equity grant as well as annual refresh grants
- Flex First remote work policy
- Regular in-person events
Salary Range
$193000 - $214000 CAD
Locations
- Canada, Canada (Remote)
Salary
193,000 - 214,000 CAD / yearly
Skills Required
- Pythonintermediate
- Ruby or Gointermediate
- REST/gRPCintermediate
- Third-party APIs (Meta, Google, The Trade Desk)intermediate
- DBTintermediate
- Airflowintermediate
- Spark/Databricksintermediate
- Advanced SQLintermediate
- Snowflakeintermediate
- AWSintermediate
- Temporalintermediate
- Event-driven patternsintermediate
- Ad-tech/programmaticintermediate
- Cleanrooms (Snowflake DCR)intermediate
- UID2, RampIDintermediate
- GDPR/CCPAintermediate
- CI/CDintermediate
- Containersintermediate
- Datadogintermediate
- GitHub Copilotintermediate
- Cursorintermediate
- OpenAI-based assistantsintermediate
Required Qualifications
- 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. (experience)
- 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). (experience)
- Data pipelines with DBT and Airflow; Spark/Databricks; advanced SQL and performance tuning. (experience)
- Snowflake and AWS experience; cost-aware design; workflow orchestration (e.g., Temporal) and event-driven patterns. (experience)
- Experience with ad-tech/programmatic and measurement integrations; cleanrooms (Snowflake DCR, shares/listings); identity/matching (UID2, RampID) and deconfliction. (experience)
- Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows. (experience)
- CI/CD, containers, test strategy; observability (metrics/logs/tracing) with tools like Datadog; incident readiness and SLO thinking. (experience)
- Demonstrated, recent hands-on use of AI-assisted development tools (e.g., GitHub Copilot, Cursor, OpenAI-based assistants) to improve speed and quality. (experience)
- Experience defining reusable prompts/workflows for team use and contributing to AI-enabled internal tools or automation. (experience)
- Ability to evaluate when to apply AI vs. deterministic systems; familiarity with evaluation, guardrails, and security/privacy implications in AI usage. (experience)
- Clear technical writing; stakeholder management; ability to drive consensus and unblock execution. (experience)
Preferred Qualifications
- Direct experience with UID2/TTD integrations, Roku/Pubmatic/NBCU, or Meta Advanced Analytics/Google ADH pipelines. (experience)
- Catalog/taxonomy, entity lineage, or custom hierarchy systems. (experience)
- Snowflake governance patterns, partner data collaboration at scale. (experience)
- Vendor/partner management and external API certification programs. (experience)
- Building AI-powered internal tools (e.g., Slackbots, data assistants). (experience)
Responsibilities
- 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).
Benefits
- general: Highly market-competitive compensation
- general: New hire equity grant as well as annual refresh grants
- general: Flex First remote work policy
- general: Regular in-person events
Tags & Categories
Senior Software Engineer II, Ads Data Solutions Engineering
Instacart
Senior Software Engineer II, Ads Data Solutions Engineering
Job Description
Responsibilities
- 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).
Required Qualifications
- 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.
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).
Required Skills
- Python
- Ruby or Go
- REST/gRPC
- Third-party APIs (Meta, Google, The Trade Desk)
- DBT
- Airflow
- Spark/Databricks
- Advanced SQL
- Snowflake
- AWS
- Temporal
- Event-driven patterns
- Ad-tech/programmatic
- Cleanrooms (Snowflake DCR)
- UID2, RampID
- GDPR/CCPA
- CI/CD
- Containers
- Datadog
- GitHub Copilot
- Cursor
- OpenAI-based assistants
Benefits
- Highly market-competitive compensation
- New hire equity grant as well as annual refresh grants
- Flex First remote work policy
- Regular in-person events
Salary Range
$193000 - $214000 CAD
Locations
- Canada, Canada (Remote)
Salary
193,000 - 214,000 CAD / yearly
Skills Required
- Pythonintermediate
- Ruby or Gointermediate
- REST/gRPCintermediate
- Third-party APIs (Meta, Google, The Trade Desk)intermediate
- DBTintermediate
- Airflowintermediate
- Spark/Databricksintermediate
- Advanced SQLintermediate
- Snowflakeintermediate
- AWSintermediate
- Temporalintermediate
- Event-driven patternsintermediate
- Ad-tech/programmaticintermediate
- Cleanrooms (Snowflake DCR)intermediate
- UID2, RampIDintermediate
- GDPR/CCPAintermediate
- CI/CDintermediate
- Containersintermediate
- Datadogintermediate
- GitHub Copilotintermediate
- Cursorintermediate
- OpenAI-based assistantsintermediate
Required Qualifications
- 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. (experience)
- 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). (experience)
- Data pipelines with DBT and Airflow; Spark/Databricks; advanced SQL and performance tuning. (experience)
- Snowflake and AWS experience; cost-aware design; workflow orchestration (e.g., Temporal) and event-driven patterns. (experience)
- Experience with ad-tech/programmatic and measurement integrations; cleanrooms (Snowflake DCR, shares/listings); identity/matching (UID2, RampID) and deconfliction. (experience)
- Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows. (experience)
- CI/CD, containers, test strategy; observability (metrics/logs/tracing) with tools like Datadog; incident readiness and SLO thinking. (experience)
- Demonstrated, recent hands-on use of AI-assisted development tools (e.g., GitHub Copilot, Cursor, OpenAI-based assistants) to improve speed and quality. (experience)
- Experience defining reusable prompts/workflows for team use and contributing to AI-enabled internal tools or automation. (experience)
- Ability to evaluate when to apply AI vs. deterministic systems; familiarity with evaluation, guardrails, and security/privacy implications in AI usage. (experience)
- Clear technical writing; stakeholder management; ability to drive consensus and unblock execution. (experience)
Preferred Qualifications
- Direct experience with UID2/TTD integrations, Roku/Pubmatic/NBCU, or Meta Advanced Analytics/Google ADH pipelines. (experience)
- Catalog/taxonomy, entity lineage, or custom hierarchy systems. (experience)
- Snowflake governance patterns, partner data collaboration at scale. (experience)
- Vendor/partner management and external API certification programs. (experience)
- Building AI-powered internal tools (e.g., Slackbots, data assistants). (experience)
Responsibilities
- 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).
Benefits
- general: Highly market-competitive compensation
- general: New hire equity grant as well as annual refresh grants
- general: Flex First remote work policy
- general: Regular in-person events
Tags & Categories