Data Engineer(8+ years)

• *Job ID: INFIT001**

• *Senior Data Engineer / Data Platform Consultant (AWS, SageMaker Unified Studio \& Life Sciences)**

Experience: 8\+ years (Minimum)

Work Timings: 11 am to 7 pm IST (flexible upon client calls)

Duration: 3 months (Will extend)

Work Model: Remote (Contractual)

Expected Joining: Immediate

If you're interested, kindly share your profile with **recruiter@inforizonhr.com**

Job Description – Senior Data Engineer / Data Platform Consultant (AWS, SageMaker Unified Studio \& Life Sciences)

Position Overview

We are seeking experienced Data Engineering and Data Platform professionals with exposure to Amazon SageMaker Unified Studio (SUS) or comparable cloud\-native data and AI platforms. The ideal candidate will have strong hands\-on experience with AWS data services and modern data architectures, along with Life Sciences domain knowledge.

Given the evolving nature of SageMaker Unified Studio, candidates with experience in the broader AWS Machine Learning ecosystem, Databricks, and AWS data services will also be considered highly relevant.

The role involves designing, building, and supporting scalable data, analytics, and AI/ML solutions while working closely with business and technical stakeholders.

Key Responsibilities

Design, develop, and maintain modern cloud\-based data platforms on AWS.

Build and optimize data pipelines, data lakes, and analytics solutions using AWS\-native services.

Work with Amazon SageMaker Unified Studio and related AWS AI/ML services to enable data science and machine learning workflows.

Implement data ingestion, transformation, and orchestration solutions across structured and unstructured data sources.

Design and support data lake architectures leveraging modern open table formats such as Apache Iceberg.

Collaborate with data scientists, analysts, and business stakeholders to deliver scalable data and AI solutions.

Implement data governance, security, and access control best practices.

Support performance tuning, monitoring, and optimization of data platforms.

Participate in architecture discussions, client engagements, and technical workshops.

Contribute to the adoption of DataOps, MLOps, and cloud engineering best practices.

Required Skills \& Experience

8\+ years of experience in Data Engineering, Data Platforms, or Cloud Data Solutions.

Strong hands\-on experience with AWS data and analytics services, including:

oAWS Glue

oAmazon Athena

oAmazon Redshift

oAmazon S3

oAWS IAM

oAWS Lake Formation (preferred)

Experience building and managing enterprise\-scale data lakes and analytics platforms.

Strong SQL and Python development skills.

Experience with ETL/ELT frameworks and data integration pipelines.

Familiarity with Apache Iceberg or other modern table formats.

Understanding of cloud security, data governance, and data access management.

Experience with Amazon SageMaker Unified Studio or the broader AWS Machine Learning ecosystem.

Hands\-on experience with

oAmazon SageMaker

oSageMaker Studio

oSageMaker Pipelines

oMLOps workflows

Experience with Databricks, Spark, or similar modern data platforms.

Knowledge of Data Lakehouse architectures.

Experience with Infrastructure as Code (Terraform, CloudFormation, CDK).

Exposure to CI/CD and DevOps practices.

Life Sciences Domain Experience (Preferred)

Candidates with experience in Life Sciences, Pharmaceuticals, Biotechnology, or Healthcare will be preferred.

Relevant experience may include

Clinical Trials and Clinical Research data

Pharmaceutical R\&D platforms

Laboratory and scientific data platforms

Regulatory and compliance\-driven data environments

Commercial analytics and patient data solutions

GxP, FDA, EMA, or other regulated data environments

Ideal Candidate Profile

Experience working with AWS data services and cloud\-native analytics platforms.

Familiarity with both Data Engineering and AI/ML platform ecosystems.

Ability to work directly with clients and business stakeholders.

Strong problem\-solving and communication skills.

Experience operating in enterprise\-scale cloud environments.

Life Sciences domain knowledge combined with AWS data platform expertise is highly desirable.

Primary Skills: AWS Data Services, AWS Glue, Athena, Redshift, S3, Apache Iceberg, SageMaker Unified Studio (or AWS ML Stack), Databricks

Preferred Domain: Life Sciences / Pharmaceuticals / Healthcare

• *Benefits**

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• *Here are some of the perks of being a part of Inforizon**
• ----------------------------------------------------------

### **Better Salary**

W offer competitive salaries to keep our employees motivated and keep a sense of unity within our company.

### **Flexibility**

Inforizon offer flexible work hours or remote work options, allowing employees to achieve a better work\-life balance.

### **Career Growth**

Inforizon invest in our employees' professional growth by providing training, education, and career opportunities.

### **Recognition**

We offer Performance bonuses and extra financial rewards based on individual and teams achievements.

### **Technology**

We help up\-to\-date tools and technology needed for the job. Equipment and software to facilitate remote work.