Data Engineer

As a data engineer with 2-4 years of experience, you’d typically find yourself in a mid-level position where you're expected to handle a variety of responsibilities related to data processing, storage, and analysis. Here’s a typical job description for a data engineer at this experience level:

Job Title: Data Engineer Experience Level: 2-4 years Job Description:
We are seeking a skilled data engineer to join our team. The ideal candidate will have 2-4 years of experience working with data pipelines, databases, and data warehousing solutions. As a data engineer, you will be responsible for designing, developing, and maintaining our data infrastructure to support our growing data needs.


Responsibilities:

†Develop and maintain data integration solutions to consolidate data from various sources (e.g., databases, APIs, flat files) into a unified format for analysis and reporting.
†Design and optimize databases to ensure efficient storage and retrieval of data.
• Collaborate with data scientists and analysts to understand data requirements and provide clean and reliable datasets for analysis.
• Monitor and troubleshoot data pipelines to ensure data integrity and reliability.
• Implement data quality checks, data profiling, and data governance practices to ensure data accuracy, consistency, and reliability across different data sets.
• Stay updated with the latest technologies and best practices in data engineering and recommend improvements to our data infrastructure.
• Document data engineering processes and workflows for knowledge sharing and future reference.


Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 2-4 years of experience working as a data engineer or in a similar role.
• Proficiency in SQL and experience with database technologies such as PostgreSQL, MySQL, or similar.

• Experience with data pipeline tools such as Apache Airflow, Flink, or similar.
• Strong programming skills in languages such as Python or Scala.
• Familiarity with cloud platforms such as AWS, Azure, or GCP and their data services (e.g., S3, Redshift, BigQuery).
• Knowledge of data modeling and ETL processes.
• Excellent problem-solving and analytical skills.
• Strong analytical, problem-solving, and communication skills, with the ability to collaborate effectively in a team environment.


Preferred Qualifications:

• Experience with big data technologies such as Hadoop, Spark, or Kafka.
• Knowledge of data governance and compliance standards.
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes.


Additional Notes:

Candidates with experience in data visualization tools (e.g., Tableau, Power BI) or machine learning frameworks may have an advantage, depending on the specific needs of the organization. The role may also involve working on data security, compliance, and privacy aspects, so knowledge of data protection regulations (e.g., GDPR, HIPAA) is beneficial.