Senior Data Engineer

• Big Data:Exposure to ‘big data’ platforms such as Hadoop, Hive or Iceberg for data storage and processing
• Data Warehousing & Database Management: Understanding of Data Warehousing concepts, Relational (Oracle, MSSQL, MySQL) and NoSQL (MongoDB, DynamoDB) database design
• Data Modeling & Design: Good exposure to data modeling techniques; design, optimization and maintenance of data models and data structures
• Languages: Proficient in one or more programming languages commonly used in data engineering such as Python, PySpark, UNIX Shell scripting
• DevOps: Exposure to concepts and enablers - CI/CD platforms, bitbucket/Github, JIRA, Jenkins, Tekton, Harness

Technical Skills (Valuable)

• Data Quality & Controls: Exposure to data validation, cleansing, enrichment and data controls, framework libraries like Deequ
• Federated Query: Starburst, Trino
• Containerization: Fair understanding of containerization platforms like Docker, Kubernetes, Openshift
• File Formats: Exposure in working on File/Table Formats such as Avro, Parquet, Iceberg, Delta
• Schedulers: Basics of Job scheduler like Autosys, Airflow
• Cloud: Experience in cloud native technologies and patterns (AWS, Google Cloud)
• Nice to have: Java, for REST API development

Other skills :

• Strong project management and organizational skills. 
• Excellent problem-solving, communication, and organizational skills. 
• Proven ability to work independently and with a team.
• Experience in managing and implementing successful projects
• Ability to adjust priorities quickly as circumstances dictate
  • Consistently demonstrates clear and concise written and verbal communication