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Data Architect With Aws & Snowflake Experience
Ampstek
Remote
BRL 30.000 - 45.000
Teilzeit
Gestern
Sei unter den ersten Bewerbenden

Zusammenfassung

A leading data solutions company is seeking a Data Architect with extensive AWS and Snowflake experience. The role includes leading a team of data engineers, owning end-to-end data pipeline solutions, and optimizing data workflows. We require 8+ years in data engineering with strong skills in Python, Snowflake, and Apache Airflow. The position is 100% remote and offers the opportunity to work on large-scale data projects in a dynamic environment.

Qualifikationen

  • 8+ years of experience in data engineering with a proven track record of leading data projects or teams.
  • Strong programming skills in Python, with expertise in building and optimizing ETL pipelines.
  • Extensive experience with Snowflake or equivalent data warehouses for designing schemas, optimizing queries, and managing large datasets.
  • Expertise in orchestration tools like Apache Airflow, with experience in building and managing complex workflows.

Aufgaben

  • Provide technical direction and mentorship to a team of data engineers.
  • Architect, implement, and optimize end-to-end data pipelines for large-scale datasets.
  • Design scalable workflows using orchestration tools, ensuring high availability and fault tolerance.
  • Lead the implementation and optimization of Snowflake and data lake technologies.

Kenntnisse

Data engineering
Python
Snowflake
Apache Airflow
Kafka
ETL pipelines
Apache Iceberg
Docker
Kubernetes
CI/CD
Agile
Data modeling

Tools

AWS
Azure
GCP
Jobbeschreibung

Title: Data Architect with AWS & Snowflake experience

Location: 100% Remote

Job Type: Contract

Responsibilities
  • Technical Leadership: Provide technical direction and mentorship to a team of data engineers, ensuring best practices in coding, architecture, and data operations.
  • End-to-End Ownership: Architect, implement, and optimize end-to-end data pipelines that process and transform large-scale datasets efficiently and reliably.
  • Orchestration and Automation: Design scalable workflows using orchestration tools such as Apache Airflow, ensuring high availability and fault tolerance.
  • Data Warehouse and Lake Optimization: Lead the implementation and optimization of Snowflake and data lake technologies like Apache Iceberg for storage, query performance, and scalability.
  • Real-Time and Batch Processing: Build robust systems leveraging Kafka, SQS, or similar messaging technologies for real-time and batch data processing.
  • Cross-Functional Collaboration: Work closely with Data Science, Product, and Engineering teams to define data requirements and deliver actionable insights.
  • Data Governance and Security: Establish and enforce data governance frameworks, ensuring compliance with regulatory standards and maintaining data integrity.
  • Scalability and Performance: Develop strategies to optimize performance for systems processing terabytes of data daily while ensuring scalability.
  • Team Building: Foster a collaborative team environment, driving skill development, career growth, and continuous learning within the team.
  • Innovation and Continuous Improvement: Stay ahead of industry trends to evaluate and incorporate new tools, technologies, and methodologies into the organization.
Qualifications
Required Skills
  • 8+ years of experience in data engineering with a proven track record of leading data projects or teams.
  • Strong programming skills in Python, with expertise in building and optimizing ETL pipelines.
  • Extensive experience with Snowflake or equivalent data warehouses for designing schemas, optimizing queries, and managing large datasets.
  • Expertise in orchestration tools like Apache Airflow, with experience in building and managing complex workflows.
  • Deep understanding of messaging queues such as Kafka, AWS SQS, or similar technologies for real-time data ingestion and processing.
  • Demonstrated ability to architect and implement scalable data solutions handling terabytes of data.
  • Hands-on experience with Apache Iceberg for managing and optimizing data lakes.
  • Proficiency in containerization and orchestration tools like Docker and Kubernetes for deploying and managing distributed systems.
  • Strong understanding of CI/CD pipelines, including version control, deployment strategies, and automated testing.
  • Proven experience working in an Agile development environment and managing cross-functional team interactions.
  • Strong background in data modeling, data governance, and ensuring compliance with data security standards.
  • Experience working with cloud platforms like AWS, Azure, or GCP.
Preferred Skills
  • Proficiency in stream processing frameworks such as Apache Flink for real-time analytics.
  • Familiarity with programming languages like Scala or Java for additional engineering tasks.
  • Exposure to integrating data pipelines with machine learning workflows.
  • Strong analytical skills to evaluate new technologies and tools for scalability and performance.
Leadership Skills
  • Proven ability to lead and mentor data engineering teams, promoting collaboration and a culture of excellence.
  • Exceptional communication and interpersonal skills to articulate complex technical concepts to stakeholders.
  • Strategic thinking to align data engineering efforts with business goals and objectives.
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