Senior Data Engineer

3 days ago

Gurgaon, Haryana, India Weekday AI (YC W21) Full time ₹ 12,00,000 - ₹ 36,00,000 per year

This role is for one of the Weekday's clients
Min Experience: 5 years

Location: Gurgaon

JobType: full-time

We are seeking an experienced
Senior Data Engineer
with strong expertise in building and managing large-scale data pipelines within the AWS ecosystem. The ideal candidate will have a solid background in SQL, cloud-native data platforms, and orchestration frameworks, with a deep understanding of scalable data lake and warehouse architectures.

Requirements
Key Responsibilities

  • Design, develop, and maintain robust, scalable data pipelines and ETL/ELT workflows.
  • Leverage the AWS Data Stack (S3, Glue, Kinesis, Redshift, Data Lake) for data ingestion, transformation, and storage.
  • Write, optimize, and manage complex SQL queries for analytics and reporting needs.
  • Implement and manage data orchestration frameworks (e.g., Airflow, Step Functions) to automate and monitor workflows.
  • Utilize Databricks for advanced data processing, transformation, and analytics.
  • Ensure data quality, integrity, reliability, and security across the pipeline lifecycle.
  • Collaborate with data scientists, analysts, and business stakeholders to deliver scalable data-driven solutions.

Required Skills & Qualifications

  • 5-7 years of proven experience as a Data Engineer or in a similar role.
  • Strong expertise in SQL development and performance optimization.
  • Hands-on experience with AWS Data Stack (S3, Glue, Kinesis, Redshift, Data Lake).
  • Proficiency in designing and managing orchestration workflows for data pipelines.
  • Experience with Databricks for data engineering and transformation.
  • Strong understanding of data modeling, warehousing concepts, and ETL/ELT best practices.
  • Ability to thrive in a hybrid working model with cross-functional collaboration.

Nice to Have

  • Experience with Python or Scala for data engineering tasks.
  • Familiarity with CI/CD pipelines and DevOps practices for data workflows.
  • Exposure to real-time streaming pipelines and advanced analytics use cases.

Core Skills
PySpark

  • SQL
  • Databricks
  • AWS

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