Analistas e Consultores: AI, Data Engineering & Media Growth
Salary not listed • Sao Paulo, Torre Paineira • Full-time
Posted 1d ago
Job Location
Sao Paulo, Torre Paineira
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
Accenture is seeking professionals for various roles within Data & AI, focusing on Media Growth, Data Engineering, and AI Engineering. These positions offer opportunities to work with leading companies, reinventing their digital core and leveraging AI for rapid value generation. The company aims to be the preferred reinvention partner, leading safe and scaled AI adoption, and fostering a customer-centric, AI-driven environment. Successful candidates will join a global team of approximately 786,000 individuals, utilizing proprietary assets and platforms to deliver integrated solutions and measurable results across diverse industries.
Responsibilities
- Analyze creative saturation, reach, frequency, auction efficiency, and delivery.
- Evaluate media quality, including viewability, brand safety, and invalid traffic (IVT).
- Recommend budget allocation across channels, campaigns, and audiences.
- Generate and validate campaign databases by cross-referencing media platform data with GA4 or Adobe Analytics.
- Analyze customer journeys, beyond last-click attribution, and page performance (landing pages, hotsites, apps).
- Design and analyze incrementality and brand lift tests (e.g., A/B, geo-lift, conversion lift).
- Build and evolve dashboards using Power BI and Looker Studio.
- Utilize generative AI to support analysis, SQL review, data exploration, creative classification, anomaly identification, and performance recommendations.
- Build and maintain media data ingestion pipelines from platforms like Meta, Google Ads, DV360, and TikTok, as well as analytics and CRM data.
- Model data into bronze, silver, and gold layers using dbt, creating unified views of media, journey, and customer data.
- Ensure data quality and observability through automated tests, data contracts, monitoring, and alerts.
- Structure the semantic layer and business metrics (e.g., ROAS, CAC, LTV, conversions).
- Automate media operations via APIs for bulk campaign, audience, and creative creation/updates.
- Incorporate LLMs and agents into operational workflows for tasks like copy variations, creative classification, search term analysis, and automatic performance summaries.
- Design, build, and deploy agentic systems, including agents with tool calling and multi-agent orchestration.
- Apply context engineering by defining data, tools, memory, and instructions for models.
- Work with hybrid search, reranking, and GraphRAG.
- Connect agents to data and systems using MCP (Model Context Protocol).
- Create and maintain evaluation pipelines, including golden datasets, LLM-as-a-judge, and regression tests.
- Operate LLMOps/AgentOps, covering prompt and agent versioning, tracing, observability, cost and latency control, model routing, and caching.
- Implement guardrails and security measures, such as prompt injection protection, structured output validation, PII/LGPD handling, and human-in-the-loop processes.
- Collaborate with Data Engineering to ensure AI-ready data, including semantic layers, metadata, quality, and governance.
- Develop using code assistants (e.g., GitHub Copilot, Claude Code, Cursor) with spec-driven development, automated tests, and code reviews.
Requirements
- Proficiency in media pre- and post-click metrics (reach, frequency, CPM, CTR, VTR, CPA, ROAS).
- Experience with advertising platforms like Meta Ads, Google Ads, DV360/CM360, TikTok Ads, Amazon Ads, and Mercado Ads.
- Familiarity with GA4 or Adobe Analytics.
- Intermediate SQL, preferably BigQuery.
- Advanced Excel or Google Sheets skills.
- Experience with Power BI, DataViz, and storytelling.
- Applied generative AI for data analysis.
- Python for data analysis.
- Experience with Retail Media platforms (Mercado Ads, Amazon Ads).
- Familiarity with CTV.
- Proficiency in Python and SQL.
- Experience with REST APIs, OAuth, and webhooks.
- Experience with media or analytics platform APIs (Meta API, Google Ads API, GA4 Data API).
- Cloud experience, preferably GCP (Cloud Functions/Run, Pub/Sub, Cloud Scheduler, BigQuery).
- Experience with dbt for transformation and modeling.
- Experience with Airflow/Composer or Dagster.
- Dimensional modeling knowledge.
- Familiarity with Git, code review, and CI/CD.
- Understanding of digital media funnels (conversions, attribution, audiences, campaign metrics).
- Experience with Snowflake or Databricks.
- Experience with Fivetran, Airbyte, or dlt.
- Experience with Terraform.
- Knowledge of FinOps, partitioning, and clustering.
- Experience with Docker.
- Solid software engineering skills in Python, including typing, Pydantic, async, automated testing, Git, and CI/CD.
- Experience with APIs using FastAPI and containers.
- SQL and familiarity with data warehouses (BigQuery, Snowflake, Databricks).
- Experience with LLM applications in production.