Lead Data Engineer
Location: Remote or Hybrid Tech Stack: Python, Scala, Java, AWS, Snowflake, Kafka
Help us shape the future of data-driven innovation.
We're searching for a seasoned Lead Data Engineer to join our technology team and take charge of building next-generation data platforms. If you're driven by solving complex problems and excited to work at the intersection of cloud, data, and scalability, this is the opportunity to make a tangible impact.
What You'll Be Doing:
- Architect and build cloud-native data solutions to power analytics, real-time processing, and intelligent applications
- Work closely with product managers and engineering teams to design and deploy high-performance data infrastructure
- Develop data pipelines using distributed technologies such as Spark, Kafka, and EMR
- Manage and optimize databases including Redshift, Snowflake, MySQL, and NoSQL systems
- Lead and mentor other engineers, promote best practices in coding and DevOps, and drive adoption of modern tools
- Conduct rigorous testing and code reviews to ensure performance, scalability, and data integrity
- Stay current with emerging data engineering tools and advocate for innovation within the team
You'll Need:
- Bachelor's degree in Computer Science, Engineering, or a related field
- 4+ years of hands-on experience building scalable applications and data infrastructure
- Solid expertise in cloud environments like AWS, Azure, or GCP
- Proven skills in languages such as Python, Java, Scala, and SQL
- Practical experience with large-scale data platforms and real-time data processing
- Familiarity with Agile methodologies and CI/CD pipelines
Bonus Points For:
- 7+ years of experience designing robust, production-grade systems
- Proficiency in Snowflake, Redshift, MongoDB, or Cassandra
- Experience with UNIX/Linux scripting, performance tuning, and workload optimization
- Background in financial tech, machine learning integration, or cross-cloud data architecture
Ready to lead from the front?
If you're passionate about building systems that make data accessible, actionable, and impactful, we'd love to hear from you.