Were looking for a versatile, talented, and highly motivated Data Engineer to join our growing team.
If youre passionate about solving complex problems, thrive in dynamic environments, and love working at the intersection of data engineering, machine learning infrastructure, and AI innovation, this role is for you.
As a Data Engineer, youll play a key role in shaping how data flows through the company, from building scalable pipelines and robust infrastructure to powering data science models and enabling internal teams with intelligent GenAI-powered tools. This is a hands-on, high-impact role with plenty of room for ownership, creativity, and growth.
This is a high-impact role where your work will shape how the company leverages data and AI. If you want to build, innovate, and push boundaries in a collaborative and fast-moving environment, wed love to meet you.
Responsibilities
Own the entire data lifecycle from understanding business needs and building reliable pipelines to ensuring data quality, observability, and performance.
Design, build, and scale modern data infrastructure including data lakes, warehouses, and complex ETL/ELT pipelines.
Integrate and consolidate diverse data sources (CRMs, APIs, databases, SaaS platforms) into a single, trusted source of truth.
Implement and manage CI/CD, observability, and infrastructure-as-code in a cloud-native environment.
Work with the data science team on their ML pipelines, giving data scientists the infrastructure and automation they need to deploy models to production with speed and confidence.
Collaborate with cross-functional teams to embed GenAI agents into business processes, creating smart workflows that boost efficiency and reduce manual work.
Develop frameworks and internal tooling that empower other teams to safely adopt AI and accelerate innovation.
Optimize data infrastructure for performance and cost-efficiency, with a focus on BigQuery optimization.
Ensure high data quality and integrity across large-scale ETL processes. Work closely with analysts, data scientists, and product managers to support data modeling, governance, and analytical initiatives.
Requirements: 5+ years of experience as a Data Engineer.
Strong programming skills in Python and SQL, with a focus on clean, maintainable, production-grade code.
Proven experience building data pipelines with Airflow.
Hands-on experience with modern analytical databases
Experience working with cloud platforms.
Solid knowledge of data modeling, database design, and performance optimization.
Strong problem-solving abilities, analytical mindset, and attention to detail.
Experience working in production-grade environments.
Excellent communication and collaboration skills.
Familiarity with modern CI/CD, observability, and infrastructure-as-code practices.
Experience with Kubernetes, Docker, and Terraform.
This position is open to all candidates.