Big Data Engineer - Scala, - Py spark, -Spark
Citi
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
Big Data Engineer - Scala, - Py spark, -Spark
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 (4-year graduate course)
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
Technical Skills (Must Have)
ETL
Hands on experience of building data pipelines. Proficiency in at least one of the
data integration platforms such as Ab Initio, Apache Spark, Talend and Informatica
Big Data
Exposure to ‘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)
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
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.
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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.------------------------------------------------------
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