Senior DataOps Engineer

4+ years of hands-on experience in Data Engineering, with a strong focus on building and optimizing data platforms and cloud platforms. Expertise in designing and building distributed systems and data pipelines, focusing on data integration, transformation, and processing using tools like Astronomer, Fivetran, DBT, and Segment. Proficiency in Python, Scala, SQL, and Spark. Solid understanding of cloud infrastructure (AWS/Azure), data platforms (Databricks, Snowflake, Redshift) with hands-on experience in Terraform. Passion for performance tuning, cost optimization, and ensuring efficient resource usage across the data platform. An outcome-oriented and highly-experimental interest in AI-driven development practices. Experience with data governance, security practices, and compliance. Experience learning new technologies, platforms, stacks, and coming up to speed quickly on large codebases. Emotional intelligence with collaboration and listening skills. Experience working in a rapid-growth or startup environment. Excellent communication skills and the ability to collaborate with distributed teams across time zones.

Build, scale, and optimize the data platform using Databricks, Spark, and various data integration tools. Design and maintain robust data pipelines with Airflow, Fivetran, DBT, Segment, and automate infrastructure using Terraform. Develop and maintain the infrastructure and automation needed to support MLOps practices. Use AI tools as a part of your fundamental workflows. Prototype, implement, and maintain team projects and features, serving as a technical expert, mentor, and leader. Build flexible and maintainable solutions while being accountable for quality, performance, and reliability. Elevate the team’s skills and knowledge by participating in technical designs and talks and reviewing and helping improve your and your colleague’s code. Contribute to constantly improving the team’s processes and best practices.