Data Architect with Snowflake, Python and Advance hands-on SQL

Ampstek; Teletrabalho; BRL 160.000 - 200.000; Tempo integral

Resumo da oferta

A data solutions company is seeking a Data Architect with extensive experience in data engineering to lead a team of data engineers. This role involves architecting and implementing robust data pipelines, optimizing Snowflake and data lake technologies, and ensuring data governance. The successful candidate will have a minimum of 8 years of experience in data engineering, strong Python skills, and a deep understanding of orchestration tools like Apache Airflow. This position is fully remote, offering the flexibility needed to thrive in today's dynamic work environment.

Qualificações

• 8+ years of experience in data engineering with a proven track record.
• Strong programming skills in Python for building ETL pipelines.
• Experience with Snowflake for managing large datasets.

Responsabilidades

• Provide technical leadership and mentorship to data engineers.
• Architect and implement end-to-end data pipelines.
• Design scalable workflows using orchestration tools.

Conhecimentos

Data Engineering

Python Programming

Snowflake

Apache Airflow

Kafka

CI/CD

Docker

Kubernetes

Ferramentas

Apache Iceberg

AWS SQS

Descrição da oferta de emprego

Title

Data Architect with Snowflake, Python and Advance hands-on SQL

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.