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Lead Data Engineer job description
A Lead Data Engineer is responsible for designing, building, and maintaining scalable data infrastructure and pipelines that enable efficient data processing and analytics. This role is critical for ensuring that organizations can leverage high-quality, reliable data to drive informed decision-making and gain competitive advantages.
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What is a Lead Data Engineer?
A Lead Data Engineer is a senior technical professional who oversees the development and implementation of data architecture, systems, and processes. They lead a team of data engineers, set technical direction, and ensure that data solutions align with business goals. This role requires expertise in big data technologies, cloud platforms, and data modeling, as well as strong leadership and project management skills.
What does a Lead Data Engineer do?
Lead Data Engineers design and build robust data pipelines to ingest, process, and store large volumes of data from various sources. They optimize data workflows for performance and scalability, implement data governance and security measures, and collaborate with data scientists and analysts to support advanced analytics and machine learning initiatives. Additionally, they mentor junior engineers, manage project timelines, and troubleshoot complex data issues to maintain system reliability.
Job Overview
Lead Data Engineer responsible for designing, building, and maintaining scalable data infrastructure and pipelines. This role requires expertise in big data technologies, cloud platforms, and data architecture to support data-driven decision making across the organization. The ideal candidate will mentor junior engineers and drive best practices in data engineering.
Lead Data Engineer responsibilities include:
1. Design and implement scalable data pipelines and ETL processes using technologies like Spark, Kafka, and Airflow
2. Architect and maintain data warehouse solutions (Snowflake, BigQuery, Redshift) and data lakes
3. Develop and optimize data models for both batch and real-time processing
4. Implement data quality frameworks and monitoring systems
5. Lead cross-functional projects with data science, analytics, and business teams
6. Manage cloud infrastructure on AWS, GCP, or Azure for data processing
7. Establish data governance and security best practices
8. Mentor junior data engineers and conduct code reviews
9. Optimize data systems for performance, cost, and scalability
10. Drive adoption of modern data engineering practices and tools
1. 7+ years of professional data engineering experience
2. Expert proficiency in Python, SQL, and one JVM language (Java/Scala)
3. Deep experience with big data technologies (Spark, Hadoop, Kafka)
4. Strong background in data modeling and database design
5. Proven experience with cloud platforms (AWS, GCP, or Azure)
6. Experience building and maintaining production data pipelines
7. Bachelor's degree in Computer Science or related technical field
8. Experience with workflow orchestration tools (Airflow, Luigi, Prefect)
9. Strong understanding of distributed systems and data architecture patterns
Preferred Qualifications
1. Master's degree in Computer Science or related field
2. Experience with real-time streaming data processing
3. Knowledge of machine learning infrastructure and MLOps
4. Previous leadership experience in mentoring junior engineers
5. Experience with containerization technologies (Docker, Kubernetes)
6. Contributions to open source data projects
7. Experience in specific industries: finance, healthcare, or e-commerce
8. Certifications in cloud platforms or data engineering
Bonus Skills
1. Experience with data mesh architecture implementation
2. Knowledge of graph databases and processing
3. Experience with serverless data processing technologies
4. Background in data governance and compliance frameworks
5. Public speaking or conference presentation experience
6. Experience with multi-cloud data architectures
7. Knowledge of advanced optimization techniques for large-scale data
8. Experience with data quality and observability platforms
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