Lead Data Engineer

We are looking for a Lead Data Engineer to drive the design and implementation of scalable data solutions, pipelines, and analytics-ready datasets. 

What You’ll Do 

• Lead design and implementation of data pipelines, transformations, and curated datasets 
• Translate business requirements into structured data solutions and models 
• Guide and execute development of reusable, analytics-ready data assets 
• Ensure consistency in how key data elements are defined and used across systems 
• Collaborate with stakeholders to define and refine data requirements and logic 
• Review and guide engineering work to ensure quality, performance, and scalability 
• Establish best practices for data engineering, transformation, and data quality 
• Support integration of data across multiple domains and systems 
• Contribute to architecture decisions across data platforms and tooling 
• Mentor and support other engineers on the team 

What You Bring 

Must-Haves 

• 5+ years of experience in data engineering, analytics engineering, or related fields 
• Strong SQL expertise and experience designing complex data transformations 
• Hands-on experience with modern data platforms (e.g., GCP BigQuery, Databricks, Snowflake) 
• Data platforms experience. ELT or ETL, orchestration such as Airflow or dbt, Spark, data warehouses and lakehouses such as Snowflake, BigQuery, or Databricks, streaming such as Kafka or Kinesis, metadata and data quality 
• Proficiency in Python 
• Strong understanding of data modeling concepts and data structuring for analytics 
• Experience working with stakeholders to define requirements and deliver data solutions 
• Ability to balance hands-on delivery with technical guidance 

Nice-to-Haves 

• Familiarity with data governance, lineage, or metadata management concepts 
• Experience working with cross-domain data (e.g., customer, product, transactions) 
• Exposure to financial services or other data-intensive industries 
• Experience supporting migration or evolution of data platforms (e.g., toward Databricks) 
• Experience with orchestration tools (e.g., Airflow, Cloud Composer) 
• Exposure to data modeling concepts (e.g., dimensional models, data marts, reusable datasets) 

What’s in It for You 

• Impact at scale. Help shape enterprise AI, software, and data programs across industries. 
• Growth and mastery. Work with a seasoned team from leading consulting and technology backgrounds. 
• Build real products. Work on production ready assets with autonomy over key technical decisions.