TRCD-26-04370

Senior Big Data / Cloud Data Engineer (AWS, PySpark) - Contract

Contract role in India for a 6–10 years data engineering professional to design and implement high-performance, scalable cloud data solutions on AWS. The role focuses on building and automating data pipelines for analytics/data science, strong SQL and data modeling from scratch, integrating data from on-prem and external REST sources, and operating/optimizing database and AWS platform components (e.g., EMR/ECS). Requires hands-on PySpark/Spark, AWS services (Glue/EMR and streaming via Kafka/Kinesis), CI/CD and IaC (Terraform/Jenkins), plus solid troubleshooting, performance tuning, and governance/access control awareness.

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Position summary

Location: India
Workplace: Remote
Employment: Contract
Experience: Minimum 6 years and Maximum 10 years

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Role overview

Why This Role Matters.

Your Impact

Deliver Enterprise Value

Help organisations solve complex business problems through modern technology, consulting expertise and measurable outcomes.

Collaboration

Work Across Teams

Collaborate with consultants, architects, engineers and client stakeholders throughout the project lifecycle.

Growth

Learn Continuously

Gain exposure to enterprise technologies, certifications, mentoring and real-world project experience.

Career Path

Grow With Ubique

Build a long-term consulting career with opportunities to take on greater responsibility and leadership over time.

Responsibilities

What You'll Be Doing.

Every role at Ubique contributes directly to solving meaningful business challenges for our clients.

Participate in architecture design and implementation of high-performance, scalable, and optimized data solutions.

Good Sql understanding with ability to create the data model from scratch.

Ensure performance, security, and availability of databases.

Prepare documentations and specifications

Handle common database procedures such as upgrade, backup, recovery, migration, etc.

Profile server resource usage, and optimize and tweak as necessary

Design, build and automate the deployment of data pipelines and applications to support data scientists and researchers with their reporting and data requirements.

Integrate data from a wide variety of sources, including on premise databases and external data sources with rest APIs and harvesting tools.

Collaborate with internal business units and data science teams on business requirements, data access, processing/transformation and reporting needs and leverage existing and new tools to provide solutions.

Effectively support and partner with businesses on implementation, technical issues, and training on the datalake ecosystem.

Work with team on managing AWS resources (EMR, ECS clusters, etc.) and continuously improve deployment process of our applications

Work with administrative resources and support provisioning, monitoring, configuration, and maintenance of AWS tools.

Technology stack

Tools & Technologies.

The platforms and technologies you'll use to build modern, enterprise-grade solutions.

PySpark

Required

Apache Spark

Required

AWS

Required

EMR

Required

Glue

Required

ECS

Required

Kafka

Required

AWS Kinesis

Required

SQL

Required

ETL

Required

Data pipelines

Required

Data lake

Required

Terraform

Required

Jenkins

Required

CI/CD

Required

Git

Required

Subversion

Required

Python

Required

Java

Required

Scala

Required

Requirements

Skills & Experience.

We value curiosity, collaboration and continuous learning. If you don't meet every requirement but believe you can make an impact, we'd still love to hear from you.

Essential

Required Qualifications

Big data engineering concepts

PySpark

Apache Spark

AWS (cloud data engineering)

AWS EMR

AWS Glue

SQL (advanced)

Data modeling (create data model from scratch)

ETL/data pipelines for analytics/reporting/data science

Performance tuning/optimization of SQL and databases

Relational database best practices and troubleshooting

Handling structured and unstructured data

Integrating data from on-prem databases and external sources (REST APIs)

CI/CD (automated build systems)

Infrastructure as Code (Terraform)

Version control (Git or Subversion)

Streaming platforms (Apache Kafka or AWS Kinesis)

Programming in Python and at least one of Java/Scala

Data structures and algorithms

Preferred

Nice to Have

AWS ECS

Configuration management tools

Jenkins (explicit CI/CD tool)

Database administration procedures (upgrade, backup, recovery, migration)

Server/resource profiling and tuning

Data governance and access control implementation

Datalake ecosystem support/training

Cost optimization / evaluating new cloud tools

What you'll gain

More Than Just A Job.

We're committed to helping every team member grow professionally, personally and technically while working on meaningful projects.

Global Exposure

Collaborate with international clients and multicultural teams on enterprise programmes.

Continuous Learning

Expand your expertise through mentoring, certifications and hands-on project experience.

Career Growth

Take ownership, develop leadership skills and grow your consulting career over time.

Flexible Working

Hybrid and remote collaboration designed around trust and delivering exceptional outcomes.

People First

Join a supportive culture where collaboration, respect and long-term relationships come first.

Enterprise Projects

Work on meaningful technology initiatives for leading organisations across industries.

Apply

Apply for Senior Big Data / Cloud Data Engineer (AWS, PySpark) - Contract

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