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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing data ingestion pipelines, data lakes, and data warehouses, while ensuring data quality and governance. Proficient in leveraging cloud platforms and orchestration tools to support scalable machine learning and generative AI applications.
Highest-signal resume keywords
Python ProgrammingAdvanced SQLData Lakes (S3, GCS, Azure Blob)Apache AirflowData Modeling
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Processing with SparkPandasPySparkETL / ELTDistributed ProcessingData VersioningData QualityScalable Data ArchitectureVector Databases (Pinecone, Weaviate, FAISS)NoSQL Databases
Tools & Technologies
DockerKubernetesCloud Platforms (AWS, GCP, Azure)Streaming with KafkaPub/Sub
Industry Keywords
Data GovernanceDataOpsFeature StoresMachine LearningGenerative AI
Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSAzureBigQueryCloudDockerETLGoogle Cloud PlatformKafkaKubernetesNoSQLPandasPySparkPythonScalaSparkSQL
About the role
Key responsibilities & impact- Build batch and streaming ingestion pipelines
- Design and structure data lakes and data warehouses
- Create optimized datasets for ML
- Implement embedding pipelines
- Build vector indexing for RAG
- Ensure data quality, governance, and security
- Optimize storage and processing costs
- Collaborate with AI Engineers to structure feature stores
- Build the infrastructure that enables Machine Learning and Generative AI applications
- Ensure data is organized, reliable, accessible, and scalable for training and inference
Requirements
What you’ll need- Programming language: Python
- Advanced SQL
- Scala (optional)
- Orchestration and transformation using Apache Airflow, dbt, and Prefect
- Data processing with Spark, Pandas, and PySpark
- Experience with Data Lakes (S3, GCS, Azure Blob)
- Experience with Data Warehouses (BigQuery, Snowflake, Redshift)
- Knowledge of NoSQL databases
- Knowledge of vector databases (Pinecone, Weaviate, FAISS)
- Streaming with Kafka and Pub/Sub
- Infrastructure with Docker and Kubernetes
- Cloud platforms (AWS, GCP, or Azure)
- Data modeling
- ETL / ELT
- Distributed processing
- Scalable data architecture
- Experience with unstructured data (text, logs, PDFs)
- DataOps concepts
- Data versioning and quality
Benefits
Comp & perks- Meal and/or food allowance of R$950.00 per month on an iFood card
- SulAmérica Medical Plan (100% paid by the company)
- MetLife Dental Plan
- Pet health insurance
- Life insurance
- TotalPass and Wellhub memberships to support physical activities anytime, anywhere
- Birthday Day Off
- Partnership with Sesc
- Partnership with OnHappy (discounts on hotels and flights)
- Partnerships with educational institutions
- Childcare reimbursement
- Work equipment
- Feedback-driven culture and professional development
- Dynamic environment with significant growth opportunities
- Payroll-deducted loan with some of the lowest interest rates
- Variable compensation in recognition of performance, results, and cultural alignment