Data Lead Engineer

Title: Data Lead Engineer – Snowflake

Location: Remote Mexico/Brazi

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.