01
TRPD-26-04623
Data Engineer – AWS
Hiring a permanent Data Engineer (3–5 years) in Bengaluru to design, build, and operate scalable AWS-based data pipelines and Snowflake data warehouse solutions. The role requires strong Python and SQL for transformations, deep Snowflake performance tuning and modeling knowledge, and hands-on experience with graph and vector databases (e.g., Neo4j/Neptune and Milvus/OpenSearch) including integration with LLM/AI workflows. Candidate should be comfortable with monitoring/troubleshooting pipelines, ensuring data quality/security, and working with Git workflows and Azure DevOps Boards in Agile teams.
Position summary
- Location
- India
- Workplace
- On-site
- Employment
- Full Time
- Experience
- Minimum 3 years and Maximum 5 years
Role overview
Why This Role Matters.
Hiring a permanent Data Engineer (3–5 years) in Bengaluru to design, build, and operate scalable AWS-based data pipelines and Snowflake data warehouse solutions. The role requires strong Python and SQL for transformations, deep Snowflake performance tuning and modeling knowledge, and hands-on experience with graph and vector databases (e.g., Neo4j/Neptune and Milvus/OpenSearch) including integration with LLM/AI workflows. Candidate should be comfortable with monitoring/troubleshooting pipelines, ensuring data quality/security, and working with Git workflows and Azure DevOps Boards in Agile teams.
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.
02
Build and optimize data warehousing solutions using Snowflake, including performance tuning and data modeling.
03
Write efficient and reusable code in Python and SQL for data transformation and processing.
04
Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements.
05
Integrate vector databases with LLM-based applications and AI workflows.
06
Monitor, troubleshoot, and improve pipeline performance and reliability.
07
Ensure data quality, integrity, and security across all stages of the pipeline.
08
Participate in code reviews, architecture discussions, and continuous improvement initiatives.
Technology stack
Tools & Technologies.
The platforms and technologies you'll use to build modern, enterprise-grade solutions.
01
AWS
Required
02
Amazon S3
Required
03
AWS Glue
Required
04
AWS Lambda
Required
05
Amazon Redshift
Required
06
Amazon EMR
Required
07
Snowflake
Required
08
Python
Required
09
SQL
Required
10
Neo4j
Required
11
Amazon Neptune
Required
12
Graph database
Required
13
Milvus
Required
14
Amazon OpenSearch
Required
15
Vector database
Required
16
LLM
Required
17
AI workflows
Required
18
Git
Required
19
Azure DevOps
Required
20
AzDO Boards
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
AWS data engineering services (S3, Glue, Lambda, Redshift, EMR)
Snowflake (architecture, data modeling, performance tuning, best practices)
Python (data pipelines, transformations)
SQL (advanced querying, transformations)
Graph databases (e.g., Neo4j, Amazon Neptune)
Vector databases (e.g., Milvus, Amazon OpenSearch)
Integrating vector databases with LLM-based applications/AI workflows
Monitoring, troubleshooting, and improving pipeline performance/reliability
Data quality, integrity, and security practices in pipelines
Version control with Git and Git workflows
Azure DevOps Boards (AzDO) for Agile backlog management
Preferred
Nice to Have
NVIDIA ecosystem knowledge for data/AI
RAPIDS libraries (cuDF, cuML, cuGraph)
CUDA-based tooling for GPU-accelerated data processing
AWS Step Functions (orchestration)
Data governance and compliance practices
Real-time processing frameworks (Kafka, Spark Streaming)
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 Data Engineer – AWS
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