We are looking for a Senior Data Infrastructure Engineer to lead the design, build, and optimization of a modern data platform. The role involves hands-on work with cloud-based data technologies, building data lakes from scratch, and managing large-scale data pipelines while ensuring high performance, cost efficiency, and reliability. You will collaborate closely with data engineers, data science, analytics, and product teams to support business needs.

Key Responsibilities:

• Design and build scalable data lakes / platforms using technologies such as Snowflake, Databricks, BigQuery, or Redshift
• Develop and optimize large-scale data pipelines for batch and streaming use cases
• Ensure high performance, scalability, and cost efficiency across data systems
• Work with complex data workflows, AI models, transformations, and orchestration
• Apply best practices in data modeling, monitoring, security, and governance
  
  

Requirements:

• 5+ years in data engineering or data infrastructure roles
• Proven experience building modern data platforms or data lakes from scratch
• Strong Python programming skills and experience with Spark / PySpark
• Knowledge of distributed systems and cloud-based architectures
• Experience with ETL/ELT processes and handling data at scale
  
  

Nice to Have:

• Experience with cloud providers (AWS, GCP, Azure)
• Familiarity with orchestration tools (Airflow, Dagster)
• Knowledge of data governance, security, and access control
• Experience supporting analytics, BI, or machine learning workloads
  
  

What We Offer:

• Ownership of end-to-end modern data platforms
• Opportunity to tackle high-impact, large-scale data challenges
• Collaborative, professional engineering environment
• Competitive compensation and benefits