Lead Data Engineer

We are looking for an experienced Lead Data Engineer to shape and scale modern data solutions for a growing organization. This role is ideal for a senior, detail-oriented individual who enjoys working in a dynamic environment, contributing both strategically and hands-on across engineering initiatives. The ideal candidate brings strong technical depth in cloud-based data platforms, a practical approach to data architecture, and the ability to guide engineers while partnering effectively with business stakeholders.

Responsibilities:

• Lead the design, development, and maintenance of scalable data pipelines and warehouse solutions using Python, Snowflake, and Azure-based technologies.
• Define data architecture standards that improve reliability, usability, and long-term scalability across the data environment.
• Drive performance tuning and optimization efforts for data processing workflows, storage structures, and query execution.
• Establish and strengthen data quality practices by implementing validation, monitoring, and governance measures across datasets and pipelines.
• Serve as a senior technical leader who can step into managerial responsibilities, providing direction, feedback, and support to engineering team members.
• Mentor engineers through code reviews, technical coaching, and knowledge sharing to elevate team capability and engineering consistency.
• Partner closely with business teams and technical stakeholders to translate operational and analytical needs into effective data solutions.
• Contribute hands-on to ETL development and cloud data platform enhancements, with exposure to Databricks considered an advantage.
• Act as a key point of coordination between business priorities and technical execution to ensure data initiatives deliver measurable value.
• Extensive experience in data engineering, including leadership responsibilities within fast-moving or smaller organizational environments.
• Strong programming skills in Python with proven success building and supporting production-grade data pipelines.
• Hands-on expertise with Snowflake and Microsoft Azure data services.
• Solid understanding of ETL processes, data warehousing concepts, and modern cloud data architecture.
• Demonstrated knowledge of data performance optimization, data modeling, and data quality best practices.
• Ability to mentor engineers and influence technical decisions across a broader team.
• Excellent communication skills with the ability to bridge business objectives and technical implementation.
• Experience with Azure Databricks is beneficial, though not required.