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