OverviewADP is hiring a Data Analytics Engineer. We\'re seeking a Data Analytics Engineer to build and maintain scalable data pipelines for payroll analytics and LLM feature engineering. You\'ll work on event-driven data ingestion, transformation pipelines, and feature store development to support AI/ML initiatives and business analytics.ResponsibilitiesData Pipeline Engineering: Design and implement event-driven data ingestion pipelines using SQS/SNS and Kafka; build Java-based integration services to consume and process events; develop and maintain Databricks-based ETL/ELT workflows.Feature Engineering for LLM & Analytics: Create feature datasets from ingested data to support LLM training and fine-tuning; design and implement feature stores using Python and SQL on Databricks; build data quality validation frameworks to ensure feature accuracy and consistency; develop data preprocessing pipelines for model training and inference.Data Platform Management: Maintain Databricks environments across multiple regions and deployment stages; optimize Spark jobs for performance and cost efficiency; implement data validation and monitoring solutions; manage canonical data models and transformation logic using SQL and PySpark.Analytics & Reporting: Build analytics-ready datasets for business intelligence and reporting; create data documentation and lineage tracking; support compliance and audit requirements through data validation pipelines.Must-Have QualificationsStrong experience with Databricks platform and Apache Spark (PySpark)Proficiency in SQL for complex data transformations and analyticsHands-on experience with event-driven architectures using AWS SQS/SNS and/or KafkaJava development experience for building integration services and event consumersPython programming skills for data processing, feature engineering, and automationExperience building ETL/ELT pipelines for large-scale data processingUnderstanding of data modeling, schema design, and data warehouse conceptsFamiliarity with CI/CD practices and version control (Git)Strong problem-solving skills for data quality and pipeline optimizationNice-to-HaveExperience preparing datasets for machine learning model training (especially LLMs)Knowledge of feature store architectures and MLOps practicesExperience with multi-region data processing and compliance requirementsBackground in data governance and data quality frameworksExperience with Databricks Delta Lake and Unity CatalogKnowledge of AWS servicesUnderstanding of data security and privacy best practicesExperience with test-driven development for data pipelinesTechnical EnvironmentLanguages: Python, SQL (Spark SQL), JavaPlatforms: Databricks, AWS (SQS/SNS, S3)Frameworks: Apache Spark, Kafka, PySparkTools: Git, pytest, Databricks CLIAbout ADP & ComplianceWhat are you waiting for? Apply today!Find out why people come to ADP and why they stay: https://youtu.be/ODb8lxBrxrY(ADA version: https://youtu.be/IQjUCA8SOoA )O modelo de trabalho adotado pela ADP é office based/presencial, com a possibilidade de trabalho em home-office por até duas vezes na semana.Considerando que as atividades desempenhadas pelos ocupantes deste cargo envolvem acesso a informações altamente confidenciais e sensíveis de clientes da ADP e de seus respectivos empregados, a ADP reserva-se o direito de conduzir checagem de histórico, de tempos em tempos, conforme autoriza o Incidente de Recurso de Revista Repetitivo nº 01 do Tribunal Superior do Trabalho, mediante consentimento do candidato/trabalhador.O modelo de trabalho adotado pela ADP é office based/presencial, com a possibilidade de trabalho em home-office por até duas vezes na semana. A ADS reserva-se o direito de conduzir checagem de histórico, conforme autorizado.
#J-18808-Ljbffr