Data Engineering Lead

Role Overview

• Design and implement cloud‑based data architecture components that align with enterprise architecture guidelines and business requirements
• Contribute to the evolution of data architecture by improving existing patterns, pipelines, and platform components
• Support “as‑is” and “to‑be” architecture documentation for data platforms and integrations
• Design, build, and maintain robust data pipelines in cloud data platforms such as Snowflake or Databricks
• Develop and optimize SQL‑based data transformations to deliver curated, analytics‑ready datasets
• Ensure data pipelines are reliable, performant, and maintainable through effective error handling, monitoring, and logging
• Build and maintain data solutions on the cloud, preferably AWS
• Provision and manage data infrastructure using Infrastructure as Code tools such as CloudFormation or Terraform
• Design and support business‑critical storage and compute environments following industry best practices
• Manage complex technical issues related to data platforms and pipelines
• Develop and enhance data applications and services by analyzing requirements and implementing effective solutions
• Build and maintain APIs using Python to support data access, ingestion, and integration with other systems
• Contribute to continuous improvement of data software through refactoring and performance optimization
• Work hands‑on with relational databases , including PostgreSQL and Microsoft SQL Server
• Design and maintain logical and physical data models that support analytics, reporting, and operational workloads
• Install, configure, and test complex database environments to ensure they meet functional and performance requirements
• Manage key components of the data management system, including data quality, consistency, and integrity
• Apply organizational data standards, governance practices, and compliance requirements in day‑to‑day development
• Elicit and analyze complex business and technical requirements through workshops, document analysis, and stakeholder discussions
• Translate business needs into practical, scalable data engineering solutions
• Collaborate closely with analysts, data scientists, and software engineers to deliver end‑to‑end data solutions
• Support information security practices by identifying and helping remediate vulnerabilities and data‑related risks
• Ensure delivered solutions comply with organizational policies, procedures, and relevant regulatory requirements
• Create and maintain high‑quality technical documentation for data pipelines, platforms, and integrations
• Share knowledge and best practices within the team through documentation and peer collaboration

Requirements

• Degree in Computer Science, Information Technology, or a related field
• 7+ years of experience in data engineering with a focus on complex data solutions
• Proven experience building and supporting cloud‑based data architecture , preferably on AWS
• Hands‑on experience with Infrastructure as Code tools such as CloudFormation or Terraform
• Strong experience developing data pipelines in Snowflake, Databricks , or similar cloud data platforms
• Strong SQL skills for data transformation, optimization, and analysis
• Experience developing APIs using Python.
• Solid hands‑on experience with PostgreSQL and Microsoft SQL Server
• Strong understanding of data modelling principles and practical application
• Experience working with large, complex datasets in production environments
• Ability to clearly communicate technical concepts and collaborate across teams

Tech Stack

• AWS
• Cloud
• MS SQL Server
• Postgres
• Python
• SQL
• Terraform

Benefits

• Health insurance
• Retirement plans
• Paid time off
• Flexible work arrangements
• Professional development