
Data Engineer Lead
4 days ago
The Data Engineer Lead is responsible for leading the design, development, and maintenance of scalable data pipelines and architectures to support analytics, reporting, and business intelligence initiatives. This role will guide a team of data engineers, ensure best practices in data management, and collaborate closely with data scientists, analysts, and stakeholders to deliver high-quality, reliable data solutions.
Key Responsibilities- Lead, mentor, and develop a team of data engineers to deliver high-quality solutions.
- Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Develop and optimize data models, data lakes, and data warehouses.
- Implement data governance, data quality, and data security standards.
- Collaborate with cross-functional teams (data scientists, analysts, product managers) to understand business needs and translate them into technical solutions.
- Evaluate, recommend, and implement modern data engineering tools and frameworks.
- Ensure efficient use of cloud platforms (e.g., AWS, Azure, GCP) and big data technologies.
- Troubleshoot and resolve issues related to data pipelines and infrastructure.
- Drive process improvements and automation in data engineering workflows.
- Provide technical leadership in architecture and solution design.
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
- 7+ years of experience in data engineering, with at least 2 years in a lead or senior role.
- Strong expertise in SQL, Python, and ETL/ELT processes.
- Hands-on experience with data warehouses (Snowflake, Redshift, BigQuery, etc.).
- Solid knowledge of big data frameworks (Hadoop, Spark, Kafka).
- Proficiency in cloud platforms (AWS, Azure, or GCP).
- Experience with CI/CD pipelines and version control (Git, Jenkins).
- Strong understanding of data governance, data quality, and security practices.
- Excellent leadership, communication, and stakeholder management skills.
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