Data Engineer

2 weeks ago


Noida, Uttar Pradesh, India DigitalCube Group Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Data Engineer

Full-time | Noida Location

Experience:
3–6 Years

Job Description
Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL processes to collect, process, and store data from various sources.
  • Work with
    Apache Spark
    to process large datasets in a distributed environment, ensuring optimal performance and scalability.
  • Develop and optimize
    Spark jobs
    and data transformations using
    Scala
    for large-scale data processing.
  • Collaborate with data analysts and other stakeholders to ensure pipelines meet business and technical requirements.
  • Integrate data from different sources (databases, APIs, cloud storage, etc.) into a unified data platform.
  • Ensure
    data quality, consistency, and accuracy
    by building robust validation and cleansing mechanisms.
  • Use
    cloud platforms (AWS, Azure, or GCP)
    to deploy and manage data processing and storage solutions.
  • Automate data workflows and tasks using appropriate tools and frameworks.
  • Monitor and troubleshoot pipeline performance, optimizing for efficiency and cost-effectiveness.
  • Implement
    data security best practices
    , ensuring privacy and compliance with industry standards.
  • Stay updated with emerging
    data engineering tools and technologies
    to continuously improve the infrastructure.

Requirements

  • 4–6 years of experience as a
    Data Engineer
    or in a similar role.
  • Strong hands-on experience with
    Apache Spark
    and
    Scala
    for distributed data processing and big data handling.
  • Basic knowledge of
    Python
    for writing data transformations and processing jobs in Spark.
  • Proficiency in
    SQL
    for querying and manipulating large datasets.
  • Experience with
    cloud data platforms
    , preferably
    AWS
    (S3, EC2, EMR, Redshift) or other cloud-based solutions.
  • Strong understanding of
    data modeling, ETL processes
    , and
    pipeline orchestration
    .
  • Familiarity with
    containerization (Docker)
    and cloud-native tools for deploying data solutions.
  • Knowledge of
    data warehousing
    concepts and experience with
    AWS Redshift, Google BigQuery, or Snowflake
    (preferred).
  • Experience with
    version control systems
    like Git.
  • Strong problem-solving skills and a proactive approach to technical challenges.
  • Excellent communication and collaboration abilities.

Preferred Qualifications

  • Experience with additional programming languages such as
    Python, Java, or Scala
    for data engineering tasks.
  • Familiarity with orchestration tools like
    Apache Airflow
    ,
    Luigi
    , or similar frameworks.
  • Basic understanding of
    data governance
    ,
    security practices
    , and
    compliance regulations
    .


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