AWS Data Architect (Standard)

AWS Data Architect (Standard) with skills Data Engineering, Python, AWS - EKS, AWS - CloudFormation, Apache Hive, Azure Storage, AWS-Apps, AWS-Infra, Azure Datalake, Azure Data Factory, AWS CloudTrail for location Any Infogain Base Location (Noida, Gurugram, Bangalore, Mumbai, Pune)

Posted on : September 26, Share on Linkedin Share on Twitter Share on Facebook

ROLES & RESPONSIBILITIES

Job Title : AWS & Data Architecture

Experience : 7–10 Years

Department : Data & Analytics

Type : Full-time

Job Summary

We are seeking a Lead Data Engineer with deep expertise in AWS data platforms , modern data architecture , and a passion for building scalable, secure, and high-performance data pipelines. This role will be responsible for architecting and overseeing the implementation of end-to-end data solutions that power analytics, reporting, and healthcare insights.

As the technical lead, you will work closely with BI teams, data analysts, and business stakeholders to ensure a robust and future-ready data infrastructure.

Key Responsibilities

Design and lead the implementation of cloud-native data architectures on AWS using services like Amazon Redshift, Glue, S3, Lake Formation, Lambda, Athena , and Step Functions .

Build and optimize ETL / ELT pipelines to process structured and semi-structured data using tools such as PySpark, AWS Glue, and Airflow .

Ensure scalability, security, and high availability of data platforms, with a focus on HIPAA-compliant healthcare data handling.

Define and implement data modeling standards , including dimensional models , star / snowflake schemas , and data lake organization .

Partner with BI and analytics teams to deliver clean, well-structured, and timely data for dashboards and insights.

Lead and mentor a team of data engineers, enforcing best practices in version control, testing, CI / CD, and documentation.

Establish and monitor data quality checks , lineage , and data cataloging using tools like AWS Glue Data Catalog , Purview , or Collibra .

Drive architectural decisions and recommend improvements in performance, cost-efficiency, and maintainability.

Support the integration of healthcare data standards (e.g., HL7, FHIR) and ensure compliance with data governance requirements.

Required Qualifications

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.

7–10 years of experience in data engineering with at least 2+ years in a technical leadership role .

Expert-level experience with AWS data services (Redshift, Glue, S3, Athena, etc.) and orchestration tools like Airflow or Step Functions .

Strong proficiency in SQL , Python , and PySpark .

Deep understanding of data architecture principles , data warehousing , lakehouse patterns , and real-time data processing .

Solid understanding of healthcare data structures and regulatory compliance (e.g., HIPAA, PHI).

Hands-on experience with DevOps for data : Git, CI / CD pipelines, infrastructure-as-code (Terraform, CloudFormation).

Preferred Qualifications

Experience with streaming technologies (e.g., Kinesis, Kafka, or AWS MSK).

Exposure to data governance platforms (e.g., Collibra, Alation, AWS Lake Formation).

Familiarity with data mesh or domain-oriented architecture .

Certifications such as AWS Certified Data Analytics – Specialty or Solutions Architect .

EXPERIENCE

• 12-14 Years

SKILLS

ABOUT THE COMPANY

Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ : MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP).

Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Kraków, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.