AWS Data Engineer

Softview Infotech; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Softview Infotech is seeking an experienced AWS Data Engineer to join our data engineering team in India. You will own design, implementation, optimization, and maintenance of data pipelines across data warehouse, data lake, and lakehouse architectures on AWS.

The role emphasizes hands‑on work with PySpark, Python, and AWS services to deliver scalable, production‑ready data solutions for customers. 3–5 years of relevant experience required in Chennai/Bangalore.

Qualifications

• 3–5 years of hands‑on experience designing, developing, and implementing data engineering solutions.
• Strong SQL development skills, including query optimization and performance tuning.
• Solid programming experience with Python.
• Proven experience building data pipelines with PySpark or Spark Scala, including streaming pipelines for near real‑time use cases.
• Hands‑on experience with AWS data engineering services like Glue, Lambda, Step Functions, Redshift, EMR, Kinesis.
• Experience with at least one NoSQL database.
• Familiarity with CI/CD pipelines and version control (Git).

Responsibilities

• Design, build, and maintain robust data pipelines across AWS data warehouse, data lake, and lakehouse environments.
• Develop and optimize batch and streaming pipelines using PySpark / Spark Scala for near real‑time analytics.
• Build and orchestrate workflows using AWS services such as Glue, Lambda, Step Functions, Redshift, EMR, and Kinesis.
• Write and tune complex SQL queries, focusing on performance and scalability.
• Apply data governance best practices across data platforms and analytics.
• Collaborate with cross‑functional teams to translate business requirements into reliable, production‑ready data solutions.
• Contribute to CI/CD pipelines and DevOps practices for data engineering components, using Git for version control.

Skills

SQL

Python

PySpark

Spark Scala

AWS services

NoSQL

Git

CI/CD

Tools

AWS Glue

AWS Lambda

Step Functions

Redshift

EMR

Kinesis

Job description

Key Skills: AWS Data Engineering, Python, Lambda

We\'re looking for an experienced AWS Data Engineer to join a fast‑paced data engineering team building scalable data solutions for our customers. In this role, you\'ll own the technical design, implementation, optimization, and maintenance of data engineering components — working across data warehouse, data lake, and lakehouse architectures on AWS. This is a hands‑on role for someone who enjoys solving complex data problems and wants to work with modern cloud‑native tooling.

• Design, build, and maintain robust data pipelines across AWS data warehouse, data lake, and lakehouse environments.
• Develop and optimize batch and streaming pipelines using PySpark / Spark Scala for near real‑time analytics.
• Build and orchestrate workflows using AWS services such as Glue, Lambda, Step Functions, Redshift, EMR, and Kinesis.
• Write and tune complex SQL queries, focusing on performance and scalability.
• Apply data governance best practices across data platforms and analytical solutions.
• Collaborate with cross‑functional teams to translate business requirements into reliable, production‑ready data solutions.
• Contribute to CI/CD pipelines and DevOps practices for data engineering components, using Git for version control.

Position: AWS Data Engineer

Experience: 3-5 Years

Location: Chennai, Bangalore

About The Role

We\'re looking for an experienced AWS Data Engineer to join a fast‑paced data engineering team building scalable data solutions for our customers. In this role, you\'ll own the technical design, implementation, optimization, and maintenance of data engineering components — working across data warehouse, data lake, and lakehouse architectures on AWS. This is a hands‑on role for someone who enjoys solving complex data problems and wants to work with modern cloud‑native tooling.

Roles & Responsibilities

• Design, build, and maintain robust data pipelines across AWS data warehouse, data lake, and lakehouse environments.
• Develop and optimize batch and streaming pipelines using PySpark / Spark Scala for near real‑time analytics.
• Build and orchestrate workflows using AWS services such as Glue, Lambda, Step Functions, Redshift, EMR, and Kinesis.
• Write and tune complex SQL queries, focusing on performance and scalability.
• Apply data governance best practices across data platforms and analytical solutions.
• Collaborate with cross‑functional teams to translate business requirements into reliable, production‑ready data solutions.
• Contribute to CI/CD pipelines and DevOps practices for data engineering components, using Git for version control.

Profile Requirements

• 3–5 years of hands‑on experience designing, developing, and implementing data engineering solutions.
• Strong SQL development skills, including query optimization and performance tuning.
• Solid programming experience with Python.
• Proven experience building data pipelines with PySpark or Spark Scala, including streaming pipelines for near real‑time use cases.
• Hands‑on experience with AWS data engineering services — Glue, Lambda, Step Functions, Redshift, EMR, Kinesis, or similar.
• Working experience with at least one NoSQL database.
• Good grasp of modern data architecture patterns and current trends in data engineering.
• Understanding of data governance principles for data platforms and analytics.
• Experience with Git for source control and CI/CD pipelines for data engineering workloads.
• Strong analytical, problem‑solving, communication, and collaboration skills.

Nice To Have

• AWS certifications, especially in data engineering / data analytics.
• Experience with Amazon AppFlow, EKS, API Gateway, or additional NoSQL database services.
• Familiarity with BI/visualization tools such as Tableau or Power BI.

Skills: aws data engineer,sql,aws data engineering,python,databricks,pyspark,lambda