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Data Architect with AWS & Snowflake experience

Ampstek

Teletrabalho

BRL 160.000 - 200.000

Tempo parcial

Há 2 dias
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Resumo da oferta

A data engineering firm is seeking an experienced Data Architect with strong expertise in AWS and Snowflake. In this remote position, you will lead data engineering projects, providing technical mentorship and focusing on end-to-end data pipeline architecture. The ideal candidate will have significant experience with Apache Airflow, data governance, and large-scale data optimization. This role requires strong programming skills in Python and the ability to work collaboratively with cross-functional teams to deliver data-driven insights.

Qualificações

  • 8+ years of experience in data engineering with leadership roles.
  • Strong programming skills in Python for ETL optimization.
  • Extensive experience with Snowflake for managing large datasets.
  • Expertise in orchestrating workflows using Apache Airflow.
  • Deep understanding of real-time messaging queues like Kafka.
  • Ability to architect scalable data solutions handling terabytes of data.
  • Hands-on experience with Apache Iceberg for data lakes management.
  • Knowledge of Docker and Kubernetes for distributed systems management.
  • Strong understanding of CI/CD pipelines and automated testing.
  • Experience in Agile development and cross-functional teamwork.
  • Proficiency in data governance and security standards compliance.
  • Experience with cloud environments like AWS or Azure.

Responsabilidades

  • Provide technical mentorship to data engineers.
  • Architect and optimize end-to-end data pipelines.
  • Design workflows with Apache Airflow, ensuring reliability.
  • Lead implementation and optimization of Snowflake technologies.
  • Build systems for real-time and batch data processing.
  • Collaborate with teams for defining data requirements.
  • Establish data governance frameworks.
  • Develop strategies for processing terabytes of data efficiently.
  • Foster team collaboration and skill development.
  • Incorporate new tools and methodologies into the organization.

Conhecimentos

Data engineering leadership
Python programming
Snowflake experience
Apache Airflow
Messaging technologies (Kafka, SQS)
Data architecture
Apache Iceberg
Docker and Kubernetes
CI/CD practices
Agile development
Data modeling
Cloud platforms (AWS, Azure, GCP)
Descrição da oferta de emprego
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.

Thanks

Aatmesh

aatmesh.singh@ampstek.com

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