Citi Group Data Engineer - C11 

India, Maharashtra, Pune 

376888587

Responsibilities

• Developing and supporting scalable, extensible, and highly available data solutions
• Deliver on critical business priorities while ensuring alignment with the wider architectural vision
• Identify and help address potential risks in the data supply chain
• Follow and contribute to technical standards
• Design and develop analytical data models

Required Qualifications & Work Experience

• First Class Degree in Engineering/Technology/MCA
• 5 to 8 years’ experience implementing data-intensive solutions using agile methodologies
• Experience of relational databases and using SQL for data querying, transformation and manipulation
• Experience of modelling data for analytical consumers

• Ability to automate and streamline the build, test and deployment of data pipelines
• Experience in cloud native technologies and patterns
• A passion for learning new technologies, and a desire for personal growth, through self-study, formal classes, or on-the-job training
• Excellent communication and problem-solving skills

echnical Skills (Must Have)

• ETL: Hands on experience of building data pipelines. Proficiency in two or more data integration platforms such as Ab Initio, Apache Spark, Talend and Informatica
• Big Data:Experience of ‘big data’ platforms such as Hadoop, Hive or Snowflake 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, Java or Scala
• DevOps : Exposure to concepts and enablers - CI/CD platforms, version control, automated quality control management

Technical Skills (Valuable)

• Ab Initio : Experience developing Co>Op graphs; ability to tune for performance. Demonstrable knowledge across full suite of Ab Initio toolsets e.g., GDE, Express>IT, Data Profiler and Conduct>IT, Control>Center, Continuous>Flows
• Cloud : Good exposure to public cloud data platforms such as S3, Snowflake, Redshift, Databricks, BigQuery, etc. Demonstratable understanding of underlying architectures and trade-offs
• Data Quality & Controls : Exposure to data validation, cleansing, enrichment and data controls
• Containerization : Fair understanding of containerization platforms like Docker, Kubernetes
• File Formats : Exposure in working on Event/File/Table Formats such as Avro, Parquet, Protobuf, Iceberg, Delta
• Others : Basics of Job scheduler like Autosys. Basics of Entitlement management
• Certification on any of the above topics would be an advantage.

Time Type:

View the " " poster. View the .

View the .

View the