The Role
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.
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
- Scala, Spark/Pyspark is must, Hadoop ( BIG Data ), + AWS,Databricks
- 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
- 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
- An inclination to mentor; an ability to lead and deliver medium sized components independently
Technical 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: Expertise around 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
- Data Governance: A strong grasp of principles and practice including data quality, security, privacy and compliance
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: Experience of using a Job scheduler e.g., Autosys. Exposure to Business Intelligence tools e.g., Tableau, Power BI
Certification on any one or more of the above topics would be an advantage.
------------------------------------------------------
Job Family Group: Technology------------------------------------------------------
Job Family:Digital Software Engineering------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
Skills Required
- Scala and Spark/PySpark proficiency
- Experience with Hadoop and big data platforms
- Experience with AWS and Databricks
- 8 to 11 years implementing data-intensive solutions
- Strong SQL skills and relational database experience
- Experience modeling data for analytical consumers
- Hands-on ETL/data pipeline development (Ab Initio, Spark, Talend, Informatica)
- Data warehousing concepts and experience with Oracle, MSSQL, MySQL
- NoSQL database experience (MongoDB, DynamoDB)
- Proficiency in one or more languages: Python, Java, Scala
- DevOps/CI-CD and version control exposure
- Knowledge of data governance, quality, security and compliance
- Experience with big data storage/processing technologies such as Hive or Snowflake
- Experience automating build, test and deployment of data pipelines
- Exposure to containerization (Docker, Kubernetes)
- Experience with file/event formats (Avro, Parquet, Protobuf, Iceberg, Delta)
- Familiarity with cloud data services (S3, Redshift, BigQuery) and BI tools (Tableau, Power BI)
- Experience tuning and developing Ab Initio Co>Op graphs
- Experience with job schedulers such as Autosys
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
-
Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
-
Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
-
Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
Citi Insights
What We Do
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.
