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Title
Text copied to clipboard!Data Pipeline Engineer
Description
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We are looking for a Data Pipeline Engineer to join our growing data engineering team. In this role, you will be responsible for building and maintaining robust, scalable, and efficient data pipelines that support our analytics, machine learning, and business intelligence initiatives. You will work closely with data scientists, analysts, and software engineers to ensure that data flows seamlessly from source systems to data warehouses and other downstream applications.
As a Data Pipeline Engineer, you will design and implement ETL (Extract, Transform, Load) processes, optimize data flow and collection for cross-functional teams, and ensure data quality and integrity across all stages of the pipeline. You will also be expected to monitor pipeline performance, troubleshoot issues, and continuously improve the architecture to support growing data needs.
The ideal candidate will have strong experience with data engineering tools and frameworks, such as Apache Airflow, Spark, Kafka, and cloud-based data platforms like AWS, GCP, or Azure. You should be proficient in programming languages such as Python, Java, or Scala, and have a solid understanding of SQL and relational databases. Familiarity with data modeling, data warehousing, and big data technologies is also essential.
This is a highly collaborative role that requires excellent communication skills, attention to detail, and a passion for working with data. You will play a key role in enabling data-driven decision-making across the organization by ensuring that high-quality data is readily available and accessible.
If you are a self-starter who thrives in a fast-paced environment and enjoys solving complex data challenges, we encourage you to apply for this exciting opportunity.
Responsibilities
Text copied to clipboard!- Design, build, and maintain scalable data pipelines
- Develop ETL processes to ingest and transform data from various sources
- Collaborate with data scientists and analysts to understand data requirements
- Ensure data quality, consistency, and integrity across all systems
- Monitor pipeline performance and troubleshoot issues
- Optimize data workflows for performance and scalability
- Implement data governance and security best practices
- Document pipeline architecture and data flow processes
- Work with cloud platforms and big data technologies
- Continuously improve pipeline architecture to support evolving data needs
Requirements
Text copied to clipboard!- Bachelor’s degree in Computer Science, Engineering, or related field
- 3+ years of experience in data engineering or related role
- Proficiency in Python, Java, or Scala
- Strong SQL skills and experience with relational databases
- Experience with ETL tools and frameworks (e.g., Apache Airflow, NiFi)
- Familiarity with big data technologies (e.g., Spark, Kafka, Hadoop)
- Experience with cloud platforms (AWS, GCP, Azure)
- Knowledge of data modeling and data warehousing concepts
- Strong problem-solving and analytical skills
- Excellent communication and collaboration abilities
Potential interview questions
Text copied to clipboard!- Can you describe your experience with building data pipelines?
- Which ETL tools and frameworks have you used?
- How do you ensure data quality and integrity in your pipelines?
- What cloud platforms have you worked with in data engineering?
- Describe a challenging data problem you solved and how you approached it.
- How do you monitor and maintain pipeline performance?
- What programming languages are you most comfortable with?
- Have you worked with big data technologies like Spark or Kafka?
- How do you collaborate with data scientists and analysts?
- What strategies do you use for optimizing data workflows?
