Senior Data Engineer

Josys

Bengaluru

On-site

INR 15,000,000 - 20,000,000

Full time

14 days+

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Job summary

A leading company is seeking a Senior Data Engineer to lead the development and maintenance of scalable data systems on AWS. The role involves designing, building, and optimizing data pipelines, ensuring data quality, and collaborating with analytics teams. Ideal candidates will have 6-8 years of experience and strong skills in Spark, Scala, Python, and AWS. This full-time position offers opportunities for mentorship and leadership in a dynamic environment.

Qualifications

6–8 years in data engineering with strong skills in Spark, Scala, Python, SQL, and AWS.
Strong understanding of data warehousing, streaming, and backend systems.

Responsibilities

Build data pipelines using Spark, Scala, and Airflow.
Manage data infrastructure on AWS and develop backend services in Node.js and TypeScript.
Implement data quality checks and design data lakes and warehouses.

Skills

Spark

Scala

Python

SQL

AWS

Airflow

Node.js

TypeScript

YAML

GitHub Actions

Kafka

Education

Bachelor’s/Master’s in Computer Science

Tools

Docker

Kubernetes

Terraform

Prometheus

Grafana

Job description

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Lead Recruiter at Josys || Building High Performance Teams || Ex. Atomicwork, Clumio and Nutanix.

We’re hiring a Senior Data Engineer (6–8 years) to lead development and maintenance of scalable data systems on AWS. You’ll work across the full data pipeline—designing, building, and optimizing for reliability, speed, and data quality—supporting analytics and business needs.

Key Responsibilities:

Build data pipelines using Spark, Scala, and Airflow (DAGs).
Clean, transform, and prepare data; automate workflows using Python.
Manage data infrastructure on AWS (S3, Redshift, EMR, Glue, Athena, IAM, EC2).
Work with the Analytics team to deliver data solutions.
Develop backend services in Node.js and TypeScript; manage configs using YAML.
Set up CI/CD with GitHub Actions; monitor and troubleshoot pipelines.
Implement data quality checks; design data lakes and warehouses.
Write and optimize SQL queries; handle OLAP/OLTP systems.
Process real-time data using Kafka or similar technologies.
Stay current with data engineering tools; mentor junior engineers.
Help define data governance and best practices.

Requirements:

Bachelor’s/Master’s in Computer Science or related field.
6–8 years in data engineering with strong skills in Spark, Scala, Python, SQL, and AWS.
Experience with Airflow, Node.js, TypeScript, YAML, GitHub Actions, and Kafka.
Strong understanding of data warehousing, streaming, and backend systems.
Excellent problem-solving and collaboration skills.

Bonus Skills:

Experience with Azure, GCP, Delta Lake, Apache Iceberg, Flink, Kinesis, Terraform, Docker, Kubernetes, Prometheus, Grafana, and data quality tools.

Seniority level