Job description
Description
- Lead the design, development, and implementation of scalable data pipelines and ELT processes using Databricks, DLT, dbt, Airflow, and other tools.
- Collaborate with stakeholders to understand data requirements and deliver high-quality data solutions.
- Optimize and maintain existing data pipelines to ensure data quality, reliability, and performance.
- Develop and enforce data engineering best practices, including coding standards, testing, and documentation.
- Mentor junior data engineers, providing technical leadership and fostering a culture of continuous learning and improvement.
- Monitor and troubleshoot data pipeline issues, ensuring timely resolution and minimal disruption to business operations.
- Stay up to date with the latest industry trends and technologies, and proactively recommend improvements to our data engineering practices.
Qualifications
Systems (MIS), Data Science or related field.10 years of experience in data engineering and / or architecture, with a focus on big data technologies.Extensive production experience with Databricks, Apache Spark, and other related technologies.Familiarity with orchestration and ELT tools like Airflow, dbt, etc.Expert SQL knowledge.Proficiency in programming languages such as Python, Scala, or Java.Strong understanding of data warehousing concepts.Experience with cloud platforms such as Azure, AWS, Google Cloud.Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.Strong communication and leadership skills, with the ability to effectively mentor and guideExperience with machine learning and data science workflowsKnowledge of data governance and security best practicesCertification in Databricks, Azure, Google Cloud or related technologies.Skills Required
Java, Scala, Mis, Sql, Python