Senior Data Engineer

Fulcrum Worldwide Software; Pune District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Fulcrum Worldwide Software is seeking a Data Engineer to design, automate, and optimize data pipelines in Python on AWS. You will build ETL processes, leverage AWS Glue/Redshift, and apply IaC with Terraform, Git workflows, and scalable architectures.

The role emphasizes performance, data quality, and collaboration with cross-functional teams, including fintech data handling, and opportunities to implement improvements across large data volumes.

Qualifications

• Strong data engineering experience with Python and SQL.
• Experience building scalable ETL pipelines for large data volumes.
• Hands-on experience with AWS services (Glue, Redshift, Lambda).
• Proficiency with Terraform and Git-based workflows.

Responsibilities

• Design, develop, and maintain efficient ETL processes using Python, SQL, AWS Glue, and Redshift.
• Automate data flows and integrations using AWS Lambda and other serverless services.
• Collaborate on scalable data architectures in AWS.
• Develop and manage infrastructure as code using Terraform.
• Participate in code reviews and collaborative version control workflows using Git.
• Document technical solutions and promote best practices in data engineering.

Skills

Python

SQL

Java

Big Data

ETL

Tools

AWS Glue

Redshift

AWS Lambda

Terraform

Git

PySpark

Job description

Role & responsibilities

Looking for a Data Engineer to join our engineering will contribute directly to the design, automation, and optimization of our data processes, primarily developing solutions in Python within the AWS cloud ecosystem, including Lambda, Glue, Redshift, and other key services.

The role also involves working with infrastructure as code (Terraform), Git-based version control, and designing scalable data architectures. The ideal candidate has solid data engineering knowledge, a passion for automation, experience working with large volumes of data, and the ability to proactively propose technical and architectural improvements. Responsibilities:

• Design, develop, and maintain efficient ETL processes using Python, SQL, AWS Glue, and Redshift.
• Automate data flows and integrations using AWS Lambda and other serverless services. Propose improvements and optimizations to existing pipelines, prioritizing performance, scalability, and maintainability.
• Collaborate on the design of scalable and resilient data architectures in AWS.
• Develop and manage infrastructure as code using Terraform.
• Actively participate in code reviews and collaborative version control workflows using Git.
• Document technical solutions and promote best practices in data engineering.
• Ensure that data processing pipelines can handle large-scale datasets (Big Data).

Technical Requirements:

• Programming Languages: Java 3+ yearsof experience(Intermediate to advanced level)
• Python 3+ years of experience (Intermediate to advanced level)
• SQL – 3+ years of experience, capable of working with complex data models

Large-scale data processing:

• Experience with PySpark or Big Data environments – 1–2+ years (preferred)
• Familiarity with distributed processing and performance optimization for high-volume data pipelines

AWS Technologies:

• Lambda, Glue, Redshift, S3 – 2–3 years of hands-on experience
• Experience designing ETL workflows using native AWS services

Infrastructure and DevOps:

• Terraform – 1–2 years of experience (Intermediate level)
• Git – Daily use in collaborative development environments

Preferred candidate profile

Well-structured project organization, error handling, logging, and automated testing within data pipelines Professional Profile:

• Proactive mindset with a drive to propose and implement improvements
• Analytical thinker with the ability to identify bottlenecks and performance issues Effective collaborator with both technical teams and non-technical stakeholders
• Strong documentation and technical communication skills

Nice to have (not mandatory):

• Experience with monitoring and observability tools for data pipelines (CloudWatch, logging, alerting) Knowledge of event-driven architecture design
• Familiarity with orchestration tools like Apache
• Experience with automated testing for data pipelines
• Background in Fintech or experience handling financial datasets
• AWS certifications are a plus

Perks and benefits