Senior Data Engineer-1521

Core Skills:

• Expertise in Big Data engineering pipelines
  
• Strong SQL and MPP Databases (Snowflake, Redshift, or BigQuery)
  
• Apache Spark (PySpark, Scala, Hadoop ecosystem)
  
• Python/Scala/Java programming
  
• Cloud Environments (AWS – S3, EMR, EC2)
  
• Data Warehousing and Data Modeling
  
• Data orchestration/ETL tools (Airflow or similar)

Responsibilities:

• Design, build, and optimize large-scale data pipelines and warehousing solutions.
  
• Develop ETL workflows in Big Data environments across cloud, on-prem, or hybrid setups.
  
• Collaborate with Data Product Managers, Architects, and Engineers to deliver scalable and reliable data solutions.
  
• Define data models and frameworks for data warehouses and marts supporting analytics and audience engagement.
  
• Maintain strong documentation practices for data governance and quality standards.
  
• Ensure solutions meet SLAs, operational efficiency, and support analytics/data science teams.
  
• Contribute to Agile/Scrum processes and continuously drive team improvements.

Qualifications:

• 6+ years of experience in data engineering with large, distributed data systems.
  
• Strong SQL expertise with ability to create performant datasets.
  
• Hands-on experience with Spark, Hadoop (HDFS, Hive, Presto, PySpark).
  
• Proficiency in Python, Scala, or Java.
  
• Experience with at least one major MPP or cloud database (Snowflake preferred, Redshift or BigQuery acceptable).
  
• Experience with orchestration tools such as Airflow.
  
• Strong knowledge of data modeling techniques and data warehousing best practices.
  
• Familiarity with Agile methodologies.
  
• Excellent problem-solving, analytical, and communication skills.
  
• Bachelor’s degree in STEM required.