Data Engineer Job at Bluelight Consulting, Brazil

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  • Bluelight Consulting
  • Brazil

Job Description

What we are looking for
  • Education & Experience
  • Education: Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent professional experience).
  • Core Experience : Proven experience developing end-to-end data pipelines extracting/transforming/loading data from REST APIs, relational databases, cloud storage, and flat files.
  • Snowflake Proficiency : Demonstrated hands-on experience with virtual warehouses, streams, tasks, stages, Snowpipe, secure data sharing, and performance optimization.
  • SQL : Advanced SQL development skills with the ability to write complex queries, tune performance, and optimize large-scale workloads.
  • Data Modeling : Experience with dimensional modeling techniques (star schemas, fact tables, dimension tables).
  • Cloud & DevOps :
  • Familiarity with cloud-based data ecosystems, particularly Microsoft Azure .
  • Managing source code and CI/CD pipelines using Git and Azure DevOps (or similar).
  • Soft Skills & Practices :
  • Strong analytical, problem-solving, and detail-oriented mindset.
  • Excellent verbal and written communication skills; ability to collaborate in a fast-paced environment with evolving priorities.
  • Knowledge of data integration best practices, data governance, and enterprise data management.
  • Preferred / Nice-to-Have
  • Certifications : SnowPro, Azure Data Engineer Associate, or equivalent cloud data platform certifications.
  • Advanced Tech : Big data technologies, machine learning, data science platforms, or advanced analytics.
  • BI Tools : Power BI, Tableau, or similar visualization platforms.
  • Methodologies : Agile delivery frameworks and DevOps practices.
  • Preferred Tech Stack Summary
  • Core : Snowflake, Python/PySpark, SQL
  • Cloud & Orchestration : Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Key Vault
  • DevOps & Infrastructure : Git, Azure DevOps, CI/CD, Infrastructure as Code (Terraform preferred)
  • Integration & Analytics : REST APIs, Power BI

Responsibilities

  • Data Engineering & ETL Development
  • Design, develop, and maintain scalable ETL/ELT pipelines using Python (PySpark) , Snowflake , and cloud-native technologies.
  • Build reliable, efficient, and reusable data ingestion, transformation, and loading processes.
  • Snowflake Data Platform & Warehousing
  • Utilize Snowflake’s architecture to design, build, and optimize modern cloud data solutions.
  • Implement and manage Snowflake objects (databases, schemas, tables, views, streams, tasks, stages, stored procedures).
  • Leverage virtual warehouses, data sharing, time travel, and automated scaling to balance performance and cost efficiency.
  • Apply dimensional modeling (star schemas, facts, dimensions) to build scalable enterprise data warehouses.
  • Data Integration & Modeling
  • Extract and ingest structured and semi-structured data from REST APIs, relational databases, SaaS apps, flat files, and cloud storage.
  • Develop robust ingestion frameworks.
  • Collaborate with data architects and stakeholders to create logical and physical data models aligned with business goals.
  • Cloud Architecture & Standards
  • Contribute to modern data platform concepts (data lakes, lakehouses, data mesh architectures, enterprise data catalogs).
  • Support integration between Snowflake and cloud-native services (primarily Azure ).
  • Establish and enforce data engineering standards and best practices.
  • Quality, Governance & Security
  • Implement automated data quality controls, validation frameworks, and monitoring processes.
  • Support data governance initiatives and maintain adherence to organizational standards.
  • Ensure data security, privacy, and regulatory compliance (access controls, masking policies, industry best practices).
  • Optimization, Operations & Maintenance
  • Monitor and optimize Snowflake workloads, ETL/ELT processes, and SQL queries to meet SLAs.
  • Analyze warehouse utilization and recommend performance and cost-efficiency improvements.
  • Monitor pipelines, diagnose performance issues, and implement long-term solutions; support production environments and incident resolution.
  • Maintain comprehensive documentation for pipelines, flows, transformations, data models, and operational processes.
  • Collaboration
  • Partner with cross-functional teams (data architects, data scientists, analysts, business stakeholders) to understand requirements and provide technical expertise.

Job Tags

Full time

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