Technical Architect-AWS Architect

Impetus; Hyderabad; Hybrid; INR 1,500,000 - 2,200,000; Full time

Job summary

Impetus is seeking a Senior Data Engineer to design scalable data engineering solutions using Python, Spark, and SQL. The role includes architecting data pipelines on AWS, mentoring junior engineers, and ensuring alignment with BFSI standards.

The ideal candidate should have strong experience in data engineering, proficiency in cloud services, and a solid understanding of AI/ML workflows. This position is key for developing robust and efficient data solutions in a highly demanding environment.

Qualifications

• 12-15 years of strong experience as a Data Engineer or in a similar technical role.
• Hands-on expertise in Python for building robust data pipelines.
• Advanced experience with Apache Spark, including performance tuning.
• Strong SQL expertise including query optimization.
• Solid experience with AWS services.

Responsibilities

• Design and develop scalable data engineering solutions using Python, Spark, and SQL.
• Architect and optimize data pipelines on AWS.
• Collaborate with stakeholders to translate BFSI domain requirements.
• Conduct code reviews, performance tuning, and solution validation.
• Mentor junior engineers and contribute to technical roadmaps.

Skills

Data engineering

Python

Apache Spark

SQL

AWS services

AI/ML workflows

Observability platforms

Cloud observability tools

Job description

Overview

Indore / Bangalore / Pune / Hyderabad

Key Responsibilities

• Design and develop scalable data engineering solutions using Python, Spark, and SQL to support high‑volume data processing needs.
• Architect and optimize end‑to‑end data pipelines on AWS, ensuring reliability, performance, and cost efficiency.
• Collaborate with stakeholders to translate BFSI domain requirements into technical architectures and data models.
• Lead the development of frameworks/project, ensuring strong governance and best practices.
• Conduct code reviews, performance tuning, and solution validation for data engineering components.
• Provide architectural guidance and support for Databricks‑based processing (good to have).
• Exp of AI/ML components, including feature engineering and model deployment support.
• Ensure solutions align with security, compliance, and data quality standards—critical for BFSI environments.
• Mentor junior engineers and contribute to technical roadmaps, documentation, and design reviews.
• Troubleshoot complex issues across data pipelines, AWS services, and distributed systems.

Required Skills & Experience

• 12-15 years of strong experience as a Data Engineer or in a similar technical role with exposure to solution design/architecture.
• Hands‑on expertise in Python for building robust data pipelines and reusable engineering components.
• Advanced experience with Apache Spark (PySpark preferred), including performance tuning and optimization.
• Strong SQL expertise—query optimization, transformations, and working with structured/semi‑structured data.
• Solid experience with AWS services such as S3, Glue, Lambda, EMR, EC2, RDS, IAM, CloudWatch, Airflow, Step Functions, etc.
• Strong understanding of observability platforms and their role in monitoring distributed systems.
• Hands‑on experience with cloud observability tools, specifically AWS CloudWatch and AWS CloudTrail
• Experience in designing data workflows in Databricks (good to have).
• Good understanding of AI/ML workflows, model lifecycle, and integration steps.

Core Skills

• Strong understanding of LLM architecture, including multi‑model/multi‑modal LLMs.
• Knowledge of LLM training concepts and RAG architecture.
• Ability to design solutions for structured & unstructured data.
• Expertise in scalable AI/LLM system design.

Good to Have

• Experience with LLM fine‑tuning (LoRA/SFT).
• Exposure to Agentic AI.
• Familiarity with AWS Bedrock.
• Mandatory BFSI domain knowledge—understanding of business processes, data types, regulatory expectations, and industry data patterns.
• Good exposure with version control (Git) and CI/CD pipelines (GitHub Actions, GitLab CI, AWS CodePipeline, Jenkins).
• Strong analytical, architectural thinking, and problem‑solving abilities.
• Excellent communication and collaboration skills, with the ability to work with business and technical teams.