Senior Data Engineer

3 days ago

Delhi, Delhi, India AagatiServe Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Experience:
5–8 Years

Location:
Delhi(Onsite)

Employment Type:
Full-time

About the Role:

We are looking for a Senior Data Engineer to join our data engineering team and help design, build, and maintain scalable data pipelines and infrastructure on AWS. The ideal candidate will have strong hands-on experience in PySpark, SQL, and AWS services, with a passion for building high-quality data solutions that power analytics, AI, and business insights.

Key Responsibilities:

  • Design, develop, and optimize large-scale data pipelines using PySpark and AWS technologies.
  • Work with stakeholders to understand data requirements and deliver efficient, reliable, and reusable data solutions.
  • Implement ETL/ELT processes to ingest, transform, and deliver data from multiple sources.
  • Ensure data quality, integrity, and performance across all systems and environments.
  • Collaborate with data scientists, analysts, and business teams to support analytics and reporting needs.
  • Monitor and troubleshoot data pipelines, ensuring scalability, availability, and cost efficiency.
  • Contribute to the architecture and design of the company's data platform, ensuring best practices in security, performance, and governance.
  • Mentor junior engineers and participate in code reviews, technical discussions, and process improvements.

Required Skills & Experience:

  • 5–8 years of experience as a Data Engineer or in a similar role.
  • Strong expertise in PySpark for data transformation and processing.
  • Advanced proficiency in SQL (query optimization, performance tuning, etc.).
  • Hands-on experience with AWS services such as S3, Glue, EMR, Redshift, Lambda, Athena, and Step Functions.
  • Strong understanding of data modeling, data warehousing, and ETL best practices.
  • Familiarity with version control (Git) and CI/CD pipelines for data engineering workflows.
  • Experience with workflow orchestration tools (e.g., Airflow, AWS Step Functions).
  • Knowledge of data governance, security, and compliance best practices.
  • Excellent communication, problem-solving, and analytical skills.

Preferred Qualifications:

  • Experience with streaming technologies (Kafka, Kinesis, Spark Streaming).
  • Knowledge of containerization (Docker, Kubernetes) and infrastructure as code (Terraform, CloudFormation).
  • Exposure to machine learning pipelines or data lakehouse architectures.
  • AWS Certified Data Analytics or Solutions Architect certification.

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