Data Engineer

3 days ago

Gurgaon, Haryana, India Digital Business People Full time ₹ 9,00,000 - ₹ 12,00,000 per year

Job Title:
Data Engineer

Location:
Gurgaon (On-site)

Experience:
4 Years

Joining:
Immediate

About the Role

We are looking for a skilled
Data Engineer
with strong expertise in
Python, AWS Cloud, and Redshift
to design, build, and maintain scalable data pipelines and solutions. The ideal candidate will have hands-on experience with large-scale data systems, cloud platforms, and database technologies, and will be able to collaborate with cross-functional teams to enable data-driven decision-making.

Key Responsibilities

  • Design, develop, and maintain
    scalable data pipelines
    and ETL processes using Python and AWS services.
  • Work with
    Amazon Redshift
    and other AWS cloud-native data solutions for data storage, processing, and analytics.
  • Ensure
    data accuracy, consistency, and availability
    across systems.
  • Collaborate with data analysts, data scientists, and business teams to provide reliable data solutions.
  • Optimize data workflows for
    performance, cost, and scalability
    .
  • Monitor and troubleshoot production data pipelines to ensure
    high availability and reliability
    .
  • Implement
    best practices
    in data engineering, including security, compliance, and performance tuning.

Required Skills & Experience

  • 4 years of experience
    as a Data Engineer or in a similar role.
  • Strong proficiency in
    Python
    for data engineering tasks.
  • Hands-on experience with
    AWS Cloud services
    (S3, Lambda, Glue, Redshift, EMR, etc.).
  • Strong knowledge of
    Amazon Redshift
    (data modeling, performance tuning, query optimization).
  • Experience in
    ETL pipeline design and development
    .
  • Strong understanding of
    SQL
    and relational databases.
  • Good problem-solving skills and the ability to work in a fast-paced environment.
  • Immediate joiner preferred.

Good to Have

  • Experience with other cloud-based data warehouses (Snowflake, Big Query).
  • Exposure to data orchestration tools like
    Airflow/Luigi
    .
  • Knowledge of CI/CD practices for data engineering.

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