Job description

🌐 About S P A Enterprise Info Services (India) Pvt. Ltd.

Founded in 2009, S P A Enterprise Info Services (India) Pvt. Ltd. is a global technology and IT consulting company, headquartered in the UK, with a strong presence across India, the USA, UAE, Canada, and Germany.

With a leadership team bringing over 1,500 years of collective global experience in SAP, Oracle, and Microsoft D365 business transformation, S P A has become a trusted partner for enterprises seeking innovation, agility, and sustainable growth.

At S P A, we don’t just deliver technology  we build possibilities.

From strategy to implementation, our experts design and manage end-to-end solutions that accelerate digital transformation and unlock business potential.

With our dual-shore delivery model, rich domain knowledge, and customer-first mindset, we help businesses enhance customer loyalty, boost profitability, and achieve operational excellence.

Recognized as a pioneer in enterprise software services, S P A delivers comprehensive SAP solutions, cutting-edge applications, and managed services for mid-sized and global organizations alike. Our solutions power industries including high-tech, retail, financial services, healthcare, and the public sector.

We are more than an IT services company  we are your transformation partner, turning vision into value and ideas into impact.

Data Engineer (Senior / Mid-Level)

Location: Hyderabad

Experience: 5+ Years (Minimum 4 Years Relevant Experience)

Role Overview

We are looking for skilled Data Engineers with strong expertise in Python, PySpark, and AWS to design, build, and optimize scalable data pipelines and cloud-based data solutions.

Key Responsibilities

Design, develop, and maintain scalable data pipelines using Python, PySpark, and Spark framework.

Build and manage data processing solutions on AWS cloud services.

Work on large-scale data ingestion, transformation, and processing.

Collaborate with cross-functional teams to understand data requirements and deliver robust solutions.

Implement data quality, validation, and monitoring mechanisms.

Optimize performance of data workflows and ensure reliability.

Participate in code reviews, testing, and deployment processes.

Primary Skills (Must-Have)

5+ years of total experience with at least 4 years in relevant Data Engineering roles.

Strong hands-on experience in:

Python and PySpark

Apache Spark framework

Minimum 2+ years of experience in AWS services, including:

AWS Lambda

Amazon S3

AWS Glue

AWS Step Functions

Amazon EventBridge

Amazon ECS / Amazon EKS

Secondary Skills (Good-to-Have)

Experience with DevOps & Infrastructure as Code (IaC) tools like Terraform.

Knowledge of CI/CD pipelines and Git.

Scripting skills in Python (preferred) or PowerShell.

Experience with code quality and security tools like SonarQube and Veracode.

Familiarity with automated testing frameworks (e.g., Pytest, ScalaTest).

Understanding of RESTful APIs and microservices architecture.

Key Competencies

Strong problem-solving and analytical skills.

Good communication and collaboration abilities.

Ability to work in agile and fast-paced environments.

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