Lead Data Engineer

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Written by AI from the job title and company, not by Dice, so some details may not match this job. The employer's own page has the real description.

Overview

The Lead Data Engineer at Dice will be responsible for the design, development, and implementation of data architecture and data modeling solutions that support the organization’s analytic needs. This role will involve leading a team of data engineers, collaborating with cross-functional teams, and providing strategic guidance on data technologies. The ideal candidate will possess robust technical skills while also being able to communicate effectively with stakeholders to ensure data quality and security are upheld throughout the data lifecycle.

Job Responsibilities

• Design and implement scalable and efficient data pipelines to ensure high-quality data flow.
• Lead a team of data engineers, mentoring members and overseeing their projects.
• Collaborate with data scientists, analysts, and business stakeholders to gather business requirements and translate them into data solutions.
• Ensure data security and compliance with regulatory requirements.
• Evaluate and implement new data engineering tools and technologies to improve data management processes.
• Monitor and optimize database performance, troubleshooting issues as they arise.
• Document data architecture and processes for internal use and stakeholder communication.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field; a Master’s degree is a plus.
• 5+ years of experience in data engineering or related roles, with a focus on large-scale data processing.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with data warehousing solutions and ETL processes.
• Strong understanding of SQL and NoSQL databases.
• Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud Platform).
• Excellent problem-solving skills and attention to detail.

Technologies & Tools

The Lead Data Engineer will utilize an array of technologies and tools including, but not limited to, Apache Hadoop, Apache Spark, ETL tools such as Talend or Informatica, SQL and NoSQL databases like PostgreSQL, MongoDB, and cloud services such as AWS Redshift or Snowflake for data warehousing and analytics. Familiarity with containerization tools such as Docker and orchestration tools like Kubernetes is also advantageous.

Ideal Candidates

The ideal candidate for the Lead Data Engineer position will display strong leadership and communication skills, enabling effective collaboration with diverse teams across the organization. They will possess a proactive attitude towards problem-solving and a keen ability to adapt to new technologies and methodologies. A passion for data integrity, security, and the pursuit of innovative data solutions will also contribute to their success in this role, making them a vital asset to Dice.