Description

You will design and build high-performance, scalable data platforms and distributed systems in an enterprise setting.

Responsibilities

• Lead high-level architecture discussions, planning sessions, and technical proposal authorship.
• Build stable, scalable systems and manage data pipelines for large-scale datasets.
• Collaborate with cross-functional teams and business partners to refine requirements and build consensus.
• Participate in code reviews, establish engineering standards, and mentor other specialists.
• Support systems and services during production incidents as part of an on-call rotation.

Required Skills

• 15+ years of big data engineering experience modeling and developing large data pipelines.
• Hands-on experience with distributed systems including Spark, HDFS, Hive, Presto, and PySpark.
• Expert-level Python and SQL skills for processing massive datasets.
• In-depth experience with AWS cloud services including S3, ECS, EMR, EC2, and Lambda.
• Proficiency with MPP or cloud database technologies such as Snowflake, Redshift, BigQuery, or Databricks.
• Strong expertise in Data Modeling techniques and Data Warehousing methodologies.
• Experience with data integration tools like Airflow and CI/CD pipelines.
• Solid understanding of computer science fundamentals, including data structures and algorithms.
• Experience using source control systems.

Preferred Skills

• Proficiency with Scrum and Agile methodologies.
• Experience directly managing and mentoring a team.

Key Skills

Education

Any Graduate