Senior Data Engineer

Description

Job Summary: We are seeking a Data Engineer to design, build, and maintain complex data architectures and pipelines, driving business intelligence in a dynamic environment. Key Highlights: 1. Dynamic and results-oriented environment 2. Ownership, autonomy, and accelerated learning 3. Building something great amid continuous evolution **About Us** **We are constantly evolving \-** strengthening our infrastructure, expanding our capabilities, and advancing to the next level of digital entertainment in Brazil. We remain pioneers — ambitious, technology-driven, and focused on scale. We operate in real time, with millions of decisions occurring every second, and we seek people who want to grow alongside this journey. Here, you will find a dynamic and results-oriented environment where ownership, autonomy, and accelerated learning are part of everyday life. We value those who leverage technology to their advantage, embrace challenges, and aim to build something significant. *If you want to join a company in continuous evolution — raising the bar and opening new opportunities — Apostou could be your next step.* **KEY RESPONSIBILITIES** * Design and build from scratch the platform’s data architecture — data warehouse, data lake, or medallion architecture — defining raw, staged, and curated layers that support all business intelligence. * Develop, deploy, and maintain data ingestion pipelines (ETL/ELT) capturing events from all critical platform sources: betting, payments, player sessions, CRM, finance, and risk — with low latency and high reliability. * Model the data warehouse and define schemas, fact tables, dimensions, and business mart areas — CRM, product, finance, risk — ensuring consistency, traceability, and query performance. * Implement and operate the data transformation stack using dbt, ensuring versioned, tested, documented, and collaboratively evolved models aligned with consuming teams. * Orchestrate all data pipelines and workflows using Apache Airflow (or equivalent), ensuring reliable scheduling, resilient reprocessing, and full visibility into dependencies. * Ensure end-to-end data quality — implementing data contracts, automated schema tests, anomaly alerts, and freshness monitoring so no consumer receives incorrect data. * Build and maintain the real-time data streaming layer for use cases such as fraud detection, responsible gaming, and CRM alerts — integrating Kafka or equivalent into the data ecosystem. * Define and implement the company’s data governance strategy: data catalog, business term dictionary, sensitive-data access control, and LGPD compliance. * Integrate BI tools — Looker, Power BI, Metabase — with the data warehouse, ensuring analysts, PMs, and leadership have self-service access to reliable, up-to-date data. * Collaborate directly with Product, CRM, Finance, Risk, and AI teams to understand analytical needs, model data correctly, and ensure infrastructure supports real-world use cases with agility. * Define and implement the company’s data engineering best practices — model versioning, quality testing, documentation, CI/CD for data — building a data-driven culture from the ground up. * Monitor the health of the entire data infrastructure — pipeline latency, cloud cost, volume of processed data — and continuously optimize for operational and cost efficiency. * Support the AI/ML team by providing features, training pipelines, and feature stores required for predictive models on churn, LTV, fraud detection, and player behavior. * Ensure data compliance with iGaming regulations — transaction auditability, sensitive data isolation, regulatory reporting — working closely with Compliance and Legal. Requirements: **What We Expect From You \- Required** * **Advanced SQL in cloud data warehouses (BigQuery, Redshift, or Snowflake) — dimensional modeling, CTEs, window functions, query optimization** * Python for data engineering — pandas, PySpark, ETL/ELT pipeline development dbt (data build tool) — layered modeling, quality testing, documentation, and model versioning * Apache Airflow or equivalent orchestrator (Prefect, Dagster) in production environments * Cloud data platform: GCP (BigQuery, Dataflow, Pub/Sub) or AWS (Redshift, Glue, Kinesis) * Kafka or streaming platform for real-time pipelines * Git and software engineering best practices applied to data (CI/CD for data, testing, code review) * **Minimum 6 years in data engineering, with experience building data warehouses or production pipelines** * Bachelor’s degree in Computer Science, Engineering, Statistics, Information Systems, or related fields * Advanced English — technical documentation, tools, and communication with vendors **Nice-to-Have Qualifications That Will Set Your Application Apart:** * **Experience in iGaming, fintechs, or high-volume transactional platforms with behavioral event streams** * Experience building data architecture from scratch — greenfield data platform Knowledge of Medallion architecture (Bronze/Silver/Gold) or Data Lakehouse (Delta Lake, Apache Iceberg) * Feature store and collaboration with ML/AI teams on training and inference pipelines * Data governance: catalog (DataHub, Amundsen, Collibra), data contracts, and LGPD applied to data * Certifications: Google Professional Data Engineer, AWS Data Analytics Specialty, or dbt Analytics Engineer * Postgraduate degree in Data Engineering, Data Science, or Software Engineering Benefits * iFood Benefits * Health Insurance * Dental Insurance * Commuting Assistance * Birthday Day Off * *Benefits applicable to CLT contracts only* *If you seek challenges, continuous learning, and want to stand out by what you deliver, grow with us.* ***We’re excited to meet you!***