Lead Consultant - AWS

Role Overview

We are seeking a highly experienced Team Lead with deep expertise in in AWS-native tools and modern data architecture . This role will lead data architecture design and implementation for client engagements, ensuring scalable, secure, and high-performing data solutions tailored to the unique data needs of life sciences commercial operations.

Key Responsibilities

Lead the technical implementation and delivery of AWS-based data solutions, ensuring alignment with business needs, performance goals, and compliance requirements.

Design and build scalable, secure, and cost-effective data pipelines, data lakes, and data warehouses using AWS-native services such as S3, Redshift, Glue, Lambda, Athena, EMR, Lake Formation , and Step Functions .

Provide hands-on expertise in SQL (advanced querying, tuning, and optimization), Apache Spark (ETL development, performance tuning, and cluster management), and end-to-end performance optimization of data pipelines, queries, and distributed data processing workloads.

Collaborate with data architects and business stakeholders to translate business requirements into technical specifications , data models, and integration designs.

Develop and maintain modular, reusable components and templates to accelerate delivery and ensure consistency across projects.

Contribute to the design and implementation of data ingestion, transformation, and analytics workflows using both batch and streaming paradigms.

Work closely with data engineers, analysts, and QA teams to ensure high-quality data delivery aligned with data governance, security, and quality standards.

Support data platform modernization initiatives , including migrations from legacy systems to cloud-native data architectures.

Promote and apply best practices for scalability, security, performance optimization, and cost efficiency in all technical implementations.

Mentor junior engineers , conduct code reviews, and foster a culture of continuous learning and technical excellence within the team.

Qualifications we seek in you :

Minimum Qualifications

industry experience, relevant years of experience in cloud-based data engineering or implementation with a focus on AWS.

Solid experience with AWS-native data services , including Glue, Redshift, S3, Lambda, and related tools.

Strong hands-on experience in Advanced SQL, Spark for large scale distributed data processing and performance tuning of ETL pipelines

Good understanding of data modeling techniques : relational, dimensional, data vault, and hybrid models.

Proven track record in leading technical delivery of end-to-end data engineering projects on AWS.

Preferred Qualifications

Exposure to additional data tools and platforms : Snowflake, Databricks (on AWS), dbt , Tableau, Power BI , etc.

Prior experience in a consulting or client-facing role is highly desirable.

AWS certification(s) such as AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Associate or Professional