Lead Data Engineer at Accellor architecting high-performance data pipelines and mentoring data engineers while collaborating on business needs and data solutions.
Responsibilities
Design and build scalable, high-performance data pipelines and architecture.
Lead and mentor a team of data engineers, fostering a culture of best practices in data management and engineering.
Collaborate with cross-functional teams to grasp business needs and translate them into technical requirements.
Ensure data quality, integrity, and security throughout the data lifecycle.
Stay updated with emerging technologies and industry trends to innovate and enhance our data practices.
Contribute to the continuous improvement of our data infrastructure and processes.
Requirements
7+ years of experience in data engineering or a related field.
Proficiency in programming languages such as Python, Java, or Scala.
Strong knowledge of SQL and experience with database technologies (e.g., PostgreSQL, MySQL).
Hands-on experience with ETL tools and data integration techniques.
Excellent understanding of data modeling concepts and best practices.
Ability to work collaboratively and communicate effectively with team members and stakeholders.
Experience with cloud platforms (AWS, Azure, GCP) is a plus.
Strong analytical, problem-solving skills, and attention to detail.
Experience with big data technologies like Hadoop or Spark is advantageous.
Certification in relevant technologies (e.g., AWS, Azure) would be beneficial.
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