Data Engineer- AWS

NECSWS; Mumbai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

NECSWS in Mumbai is looking for an experienced AWS Data Engineer to design and build cloud-native data pipelines that provide real-time insights and streamline enterprise operations.

The successful candidate will have 4–7 years of experience in data engineering, with expertise in Python, SQL, AWS, and big data technologies. You’ll develop and optimize data workflows while collaborating across teams to ensure secure and high-quality data solutions.

Qualifications

• 4–7 years of experience in application development and data engineering.
• 3+ years of experience with big data technologies.
• 3+ years of experience with cloud platforms (AWS, Azure, GCP acceptable).

Responsibilities

• Develop, test, deploy, and troubleshoot cloud-based data pipelines.
• Collaborate with cross-functional teams to integrate data from various sources.
• Ensure data integrity and maintain high data quality standards.

Skills

Python

SQL

Scala

Java

Hadoop

Hive

Kafka

Spark

MongoDB

Cassandra

Redshift

UNIX/Linux

PySpark

Agile

Education

Bachelor’s Degree in Computer Science, Engineering, or related field

Tools

AWS

Airflow

AWS Step Functions

Luigi

KubeFlow

Job description

Role Overview

We are seeking an AWS Data Engineer with 4–7 years of experience to design and build cloud-native data pipelines, contribute to innovation in data engineering practices, and collaborate across teams to deliver secure, scalable, and high-quality data solutions. This role is critical to enabling real-time insights and supporting our mission to streamline enterprise operations.

Key Responsibilities

• Develop, test, deploy, orchestrate, monitor, and troubleshoot cloud-based data pipelines and automation workflows in alignment with best practices and security standards.
• Collaborate with data scientists, architects, ETL developers, and business stakeholders to capture, format, and integrate data from internal systems, external sources, and data warehouses.
• Research and experiment with batch and streaming data technologies to evaluate their business impact and suitability for current use cases.
• Contribute to the definition and continuous improvement of data engineering processes and procedures.
• Ensure data integrity, accuracy, and security across corporate data assets.
• Maintain high data quality standards for Data Services, Analytics, and Master Data Management.
• Build automated, scalable, and test-driven data pipelines.
• Apply software development practices including Git-based version control, CI/CD, and release management to enhance AWS CI/CD pipelines.
• Partner with DevOps engineers and architects to improve DataOps tools and frameworks.

Basic Qualifications

• Bachelor’s Degree in Computer Science, Engineering, or related field.
• 4–7 years of experience in application development and data engineering.
• 3+ years of experience with big data technologies.
• 3+ years of experience with cloud platforms (AWS preferred; Azure or GCP also acceptable).
• Proficiency in Python, SQL, Scala, or Java (3+ years).
• Experience with distributed computing tools such as Hadoop, Hive, EMR, Kafka, or Spark (3+ years).
• Hands-on experience with real-time data and streaming applications (3+ years).
• NoSQL database experience (MongoDB, Cassandra) – 3+ years.
• Data warehousing expertise (Redshift or equivalent) – 3+ years.
• UNIX/Linux proficiency including shell scripting – 3+ years.
• Familiarity with Agile engineering practices.
• SQL performance tuning and optimization – 3+ years.
• PySpark experience – 2+ years.
• Exposure to process orchestration tools (Airflow, AWS Step Functions, Luigi, or KubeFlow).

Preferred Qualifications

• Experience with Machine Learning workflows.
• Exposure to Data-as-a-Service platforms.
• Experience designing and deploying APIs.