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, Cloud Formation, 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.