Data Engineer, Citi

Citi

Location:
India, Pune

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

Not provided

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Job Description:

The Data Engineer is accountable for developing high-quality data products to support the Bank’s regulatory requirements and data-driven decision making. A Data Engineer will serve as an example to other team members, work closely with customers, and remove or escalate roadblocks. By applying their knowledge of data architecture standards, data warehousing, data structures, and business intelligence they will contribute to business outcomes on an agile team.

Job Responsibility:

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.

Requirements:

First Class Degree in Engineering/Technology (4-year graduate course)
8 to 11 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
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
An inclination to mentor
an ability to lead and deliver medium-sized components independently
Hands-on experience of building data pipelines
Proficiency in data integration platform Apache Spark
Experience of ‘big data’ platforms such as Hadoop, Hive or Snowflake for data storage and processing
Expertise around Data Warehousing concepts
Relational (Oracle, MSSQL, MySQL) and NoSQL (MongoDB, DynamoDB) database design
Good exposure to data modeling techniques
design, optimization and maintenance of data models and data structures
Proficient in one or more programming languages commonly used in data engineering such as Python, Java or Scala
Knowledge of Unix shell scripting
Exposure to concepts and enablers (CI/CD platforms, version control, automated quality control management)
Strong grasp of principles and practices including data quality, security, privacy and compliance
Experience on scheduling tools such as Autosys and Cron
Exposure to data validation, cleansing, enrichment, and data controls
Experience with file formats such as Avro, Parquet, Protobuf, Iceberg, Delta.

Nice to have:

Exposure to Spring Boot, Maven, RESTful API and microservices
Good exposure to public cloud data platforms such as S3, Snowflake, Redshift, Databricks, BigQuery
Fair understanding of containerization platforms like Docker, Kubernetes
Certification on any one or more of these topics.

Additional Information:

Job Posted:
September 23, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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Data Engineer