Lead Engineer Software

Role Overview

As a Lead Data Engineer, you will play a critical role across the full data lifecycle—from business requirements gathering and data modeling to solution architecture, development, deployment, and production support. This is a hands-on technical leadership role requiring deep expertise in building scalable, cloud-native data platforms using Snowflake, Amazon Redshift, AWS, and modern data engineering tools.

What You Will Do

Design, develop, and implement scalable batch and real-time data pipelines using Snowflake, Amazon Redshift, and AWS-native technologies. Lead end-to-end data engineering initiatives including data ingestion, transformation (ETL/ELT), data quality, and data delivery across enterprise platforms.

Why It Might Be a Fit

The ideal candidate is passionate about solving complex data challenges, mentoring engineering teams, and enabling enterprise-scale analytics and AI initiatives.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field
• 12+ years of experience in Data Engineering, Data Warehousing, and Software Development
• Strong expertise in SQL and Python with experience building enterprise-scale data solutions
• Hands-on experience with Snowflake and Amazon Redshift in large-scale production environments
• Strong experience with modern data transformation frameworks such as dbt
• Experience with orchestration and workflow tools such as Apache Airflow
• Hands-on experience with streaming and CDC technologies such as Kafka, STRIIM, or similar event-streaming platforms
• Experience building and supporting observability frameworks using Datadog or equivalent monitoring platforms
• Familiarity with Vector Databases and AI/GenAI integration patterns for intelligent data applications
• Exposure to GenAI tools, LLM-powered workflows, or AI-enabled analytics platforms is highly preferred
• Strong understanding of dimensional and normalized data modeling techniques
• Experience working with AWS cloud services including S3, Lambda, Glue, IAM, ECS, CloudFormation, and related technologies
• Knowledge of CI/CD implementation using tools such as GitHub Actions, Jenkins, Terraform, or similar platforms
• Experience with data governance, data quality frameworks, and security best practices
• Excellent problem-solving, analytical, and communication skills
• Proven ability to lead technical initiatives and mentor engineering teams
• Passion for innovation, continuous learning, and adopting modern data engineering practices

Benefits

• Flexible work environment
• Fluid career paths
• Internal mobility
• Purpose, well-being, and work-life balance
• Welcoming and inclusive environment
• Volunteering opportunities