Data Engineer

As a data engineer with 3-5 years of experience, youd 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 3-5 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.