Senior Data Engineer
4 days ago
Role Title: Data Engineer / Analytics Engineer
Skillset Required (AWS | Python/Go | ETL | Reporting)
Overview
We are looking for a skilled Senior Data Engineer / Analytics Engineer to design, build, and maintain scalable data pipelines and reporting solutions. The ideal candidate will have hands-on experience with modern ETL frameworks, databases, and reporting tools, along with a solid understanding of cloud-based architectures on AWS.
You will work closely with cross-functional teams to ensure data reliability, availability, and accessibility to support business insights and analytics.
Key Responsibilities
Design, develop, and maintain data ingestion and transformation pipelines using ETL tools such as Apache NiFi, AWS Glue, or equivalent.
Build and optimize data storage solutions leveraging SQL and NoSQL databases.
Develop automated data workflows integrating multiple data sources and ensuring data quality and consistency.
Implement monitoring, alerting, and reporting dashboards using Grafana, Tableau, or Amazon QuickSight.
Collaborate with data analysts, product teams, and engineers to deliver reliable and timely datasets for analytics and reporting.
Manage source control, CI/CD, and infrastructure deployment using Git, Jenkins, and AWS services (Lambda, S3, ECS, etc.).
Ensure data security, compliance, and best practices across all environments.
Qualifications
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
7-9 years of experience in data engineering, analytics, or related domains.
Strong programming skills in Python or Go.
Hands-on experience with ETL tools (NiFi, Glue, or similar).
Proficiency in SQL and NoSQL databases.
Experience building dashboards or visualizations using Grafana, Tableau, or QuickSight.
Familiarity with AWS ecosystem, Git, and Jenkins for CI/CD.
Strong problem-solving, analytical, and communication skills.
Preferred Skills
Experience with data modeling and schema design.
Knowledge of data governance and metadata management.
Exposure to containerized environments (Docker, ECS, or Kubernetes).
Understanding of real-time data streaming (Kafka, Kinesis) is a plus.
Job Types: Full-time, Permanent
Pay: ₹700, ₹1,200,000.00 per year
Work Location: In person
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