Data Engineer - Databricks Job Description Template
The Data Engineer - Databricks will be responsible for building and optimizing our data pipelines, architectures, and data sets. You will work closely with data scientists, analysts, and other engineers to support their data needs and maximize the value of our data processing capabilities.
Responsibilities
- Design, develop, and maintain scalable and robust data pipelines on Databricks.
- Collaborate with data scientists and analysts to understand data requirements and deliver solutions.
- Optimize and troubleshoot existing data pipelines for performance and reliability.
- Ensure data quality and integrity across various data sources.
- Implement data security and compliance best practices.
- Monitor data pipeline performance and conduct necessary maintenance and updates.
- Document data pipeline processes and technical specifications.
Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in data engineering.
- Proficiency with Databricks and Spark.
- Strong SQL skills and experience with relational databases.
- Experience with big data technologies (e.g., Hadoop, Kafka).
- Knowledge of data warehousing concepts and ETL processes.
- Excellent problem-solving and analytical skills.
Skills
- Databricks
- Apache Spark
- SQL
- Python
- Data Warehousing
- ETL
- Hadoop
- Kafka
Frequently Asked Questions
A Data Engineer specializing in Databricks is responsible for designing, building, and maintaining pipelines that transform raw data into actionable insights in the Databricks environment. They utilize tools like Apache Spark to manage large datasets, optimize data flow, and ensure efficient data processing. This role also involves collaborating with data scientists and analysts to facilitate data accessibility and quality within Databricks.
To become a Data Engineer specializing in Databricks, candidates typically need a bachelor's degree in computer science, information technology, or a related field. They should gain experience with big data technologies and platforms like Apache Spark, SQL, and Python. Familiarity with Databricks and cloud platforms such as AWS or Azure is crucial. Certifications in Databricks or related technologies can enhance a candidate's prospects.
The average salary for a Data Engineer specializing in Databricks varies based on location, experience, and the hiring organization. Generally, it is competitive, reflecting the specialized skills and high demand. In metropolitan areas, salaries tend to be higher and they often include additional benefits such as bonuses and stock options, acknowledging the critical role in managing data infrastructure.
A Data Engineer focusing on Databricks typically requires a combination of academic qualifications and technical skills. A degree in computer science or a related field is usually necessary, along with proficiency in languages like Python or Scala. Experience with data pipelines, cloud services, and specific Databricks features, such as its version of Apache Spark and integrations with data storage solutions, are often essential.
Key skills for a Data Engineer specializing in Databricks include expertise in data architecture, proficiency with big data tools such as Apache Spark, and experience with cloud computing platforms. Responsibilities involve creating scalable data solutions within Databricks, optimizing data processes, and ensuring data quality. A strong understanding of ETL processes, data modeling, and collaboration with data science teams is also important.