Lead Data Engineer

About the Role

We’re looking for a Lead Data Engineer to take ownership of the architecture and delivery of data solutions in a modern, cloud-based environment. You will lead technical direction, mentor team members, and collaborate closely with cross-functional teams to ensure scalable, reliable, and high-performance data platforms.

Key Responsibilities

• Design and build robust data pipelines, ETL/ELT workflows, and data architecture

• Lead the engineering team in best practices, code quality, and solution design

• Collaborate with stakeholders, product owners, and architects to define data strategies

• Set and enforce standards around data governance, quality, and performance

• Review code, provide technical mentorship, and support engineering growth

• Take ownership of end-to-end solution delivery — from data ingestion to consumption

• Support DevOps, CI/CD, and cloud infrastructure related to data workloads

Requirements

• 6+ years of experience in Data Engineering

• Proven experience in a technical leadership or lead engineer role

• Expert in Python, SQL, and cloud-native data processing tools

• Strong knowledge of AWS (preferred), GCP or Azure also welcome

• Experience with orchestration tools (Airflow, Dagster, etc.)

• Proficiency with modern data platforms like Databricks, Snowflake, Redshift

• Familiar with data modeling, data lakes, lakehouse architectures, and streaming (Kafka, Kinesis, etc.)

• Knowledge of CI/CD, Terraform, and GitOps workflows

Nice to Have

• Experience with team management or mentoring junior engineers

• Knowledge of dbt, Spark, Delta Lake, Glue, or similar

• Exposure to MLOps, analytics engineering, or BI/data visualization tools

• Understanding of data security, compliance, and privacy regulations