Data Engineer Specialist

7 hours ago


Delhi, Delhi, India ANLAGE Full time

Data Engineer Role Overview

We are seeking a highly skilled Data Engineer to support the growth and development of our data infrastructure at ANLAGE. The ideal candidate will have a strong background in Scala programming, distributed data processing frameworks, and a deep understanding of data architecture and pipelines.

Key Responsibilities

  1. Design, develop, and maintain efficient, reliable, and scalable data pipelines using Scala and distributed frameworks like Apache Spark or Kafka.
  2. Integrate data from various sources into data lakes or data warehouses, ensuring high data quality and performance.
  3. Optimize existing processes and code for performance, scalability, and reliability, especially in distributed environments.
  4. Help define and implement data architecture that supports business analytics, machine learning, and reporting needs.
  5. Collaborate closely with data scientists, analysts, and other engineers to translate data requirements into technical solutions.
  6. Build tools and processes for monitoring, alerting, and ensuring the reliability of the data infrastructure.
  7. Write unit, integration, and end-to-end tests for data pipelines and ensure data integrity across systems.
  8. Provide clear, concise documentation for both technical and non-technical stakeholders.

Requirements

  1. Experience: 7+ years of experience in data engineering, with a focus on Scala and big data technologies.
  2. Programming Languages: Proficient in Scala; experience with Java, Python, or other JVM-based languages is a plus.
  3. Big Data Frameworks: Hands-on experience with Apache Spark, Kafka, Hadoop, or similar frameworks.
  4. Data Storage Systems: Experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Cassandra, HBase).
  5. Data Warehousing: Familiarity with data warehousing solutions like Amazon Redshift, Google BigQuery, or similar.
  6. Cloud Platforms: Experience with cloud-based data platforms (AWS, Azure, GCP).
  7. Data Processing: Strong understanding of distributed data processing, batch, and streaming data processing techniques.
  8. Version Control: Proficiency in using version control systems like Git.
  9. Problem-Solving Skills: Strong analytical and problem-solving skills with a focus on continuous improvement.
  10. Communication: Excellent communication and teamwork skills, with the ability to translate technical issues into business context.

Preferred Qualifications



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