Lead the design, build, and optimization of a modern data platform, managing large-scale data pipelines and collaborating with various teams.
Description
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
- 3-5 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
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