Data Engineer

Job Description:

We are seeking an experienced Data Engineer to join our dynamic team. The ideal candidate

will be responsible for designing, developing, and maintaining scalable data pipelines and

infrastructure for both batch and real-time data processing. You will collaborate closely with

cross-functional teams including data scientists, analysts, and product managers to understand

data requirements and deliver robust solutions that meet business needs.

Responsibilities:

• Design, build, and maintain efficient and reliable data pipelines to move and

transform data across multiple systems.

• Implement data integrations, ETL processes, and data warehouse solutions.

• Develop and optimize data models for flexibility and scalability.

• Collaborate with stakeholders to understand data requirements and propose optimal

solutions.

• Ensure data quality and reliability through monitoring, testing, and validation.

• Troubleshoot data-related issues and performance bottlenecks.

• Stay current with emerging technologies and industry trends related to data

engineering and analytics.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or related field; or equivalent

practical experience.

• 5+ years of experience in data engineering roles, with a proven track record of

designing and implementing complex data solutions.

• Proficiency in programming languages such as Python, Java, Scala, etc.

• Experience with big data technologies (Hadoop, Spark, Kafka, etc.) and cloud

platforms (AWS, Azure, GCP).

• Strong SQL skills and experience working with relational databases and data

warehouses (e.g., MySQL, PostgreSQL, Redshift).

• Familiarity with data pipeline orchestration tools (Airflow, Luigi, etc.) and version

control systems (Git, SVN, etc.).

• Excellent problem-solving and analytical skills.

• Strong communication and collaboration skills; ability to work effectively in a team

environment.

Preferred Qualifications:

• Master’s degree in Computer Science, Engineering, or related technical field.

• Experience with containerization (Docker, Kubernetes) and microservices

architecture.

• Knowledge of machine learning and data science concepts.

• Certifications in relevant technologies (AWS Certified Big Data - Specialty, Google

Professional Data Engineer, etc.).