Data Lake Architect

The ideal candidate

will have 7-8 years of experience in data architecture and a proven track record of taking

ownership of existing data platforms. This is a unique opportunity to shape our future data

strategy, optimize our current data lake, and build a high-performing team from the ground up

to support our business needs.

Key Responsibilities

Platform Takeover and Optimization: Assume responsibility for our existing AWS-

based data lake, which has been in production for three years. Conduct a

comprehensive review of the current architecture, identify areas for improvement in

performance, cost, and security, and lead the technical roadmap for optimization.

In-House Team Building: Recruit, hire, and mentor a new team of data engineers and

developers. Establish best practices for data engineering, CI/CD, and operations to

ensure the team can effectively manage the data platform.

Architectural Evolution: Evolve the existing data lake architecture to meet the

growing needs of the business. This includes designing and implementing new data

pipelines, integrating new data sources, and upgrading existing services to leverage

the latest AWS features.

Hands-on Development: Act as a lead engineer, contributing to key development

tasks, building core data pipelines, and creating infrastructure-as-code (IaC)

templates. You will set the technical standard for the team.

Collaboration and Strategy: Work closely with cross-functional teams, including

product managers, data scientists, and business stakeholders, to understand

requirements and deliver data solutions that drive business value.

Governance and Security: Enhance and enforce data governance, quality, and

security frameworks to ensure the integrity and compliance of our data assets.

Mentorship & Best Practices: Act as a subject matter expert, staying up-to-date with

the latest AWS services and industry trends, particularly in the AI space. Champion

best practices for data modeling, ETL/ELT, and data pipelines across the organization.

Qualifications

Experience: 5-8 years of progressive experience in data architecture, with at least 2-3

years in a leadership or senior architect role.

Platform Ownership: Proven experience in taking over, managing, and optimizing a

complex data platform from a third-party provider or external team.

AWS Expertise: Deep, hands-on expertise with AWS data services, including:

o Data Ingestion & Storage: S3, Glue, Kinesis, DMS, Lambda.

o Data Processing & Warehousing: EMR, Athena, Redshift, Spark.

o Orchestration & Automation: Step Functions, CloudFormation, Terraform.

o Security & Governance: IAM, KMS, Lake Formation.

Technical Skills: Strong proficiency in Python and SQL. Experience with big data

technologies and distributed computing frameworks.

Leadership: Proven experience in leading and mentoring a technical team, with

excellent communication and interpersonal skills.

Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a

related field. AWS professional-level certifications (e.g., AWS Certified Data Analytics -

Specialty, AWS Certified Solutions Architect - Professional) are highly preferred.