FIS
fintech
SeniorLeadDataEngineer
“Senior Lead Data Engineer at FIS. Skills: Data engineering, Backend development, PySpark, SQL, Snowflake/Databricks/similar, Cloud data warehousing, Apache Spark, Apache Iceberg, Dimensional modelling, Python, AWS/Azure. Key contributor in datalake journey. Transitioning Payment Hub data from OLTP to datalake”
What You'll Achieve.
Key contributor in our datalake journey; Play a key role in transitioning Payment Hub data from OLTP to datalake; Using it for various analytics and AI/ML initiatives
Industry & Context.
What They're Looking For.
Must Have
10+ years data engineering, backend development, or full-stack analytics platform work, Expert-level PySpark, SQL, and cloud data warehousing (Snowflake/Databricks/similar), Apache Iceberg or willingness to learn advanced table formats, Dimensional modelling fundamentals (Kimball star schema, slowly changing dimensions), Python for data transformation and microservices, API design, error handling, and testing discipline, Proficiency in building and maintaining CI/CD pipelines using tools like Jenkins or Azure DevOps., Experience with cloud platforms (AWS or Azure) and their services (e. g. , EC2, S3, Lambda, AKS)., understanding of testing methodologies and experience with automated testing frameworks., Should be able to perform tasks individually with ownership
Nice to Have
Advanced data architecture (data lakes, dimensional modeling), Cloud-native pipelines (AWS/Azure, serverless, ETL orchestration), DataOps (CI/CD, monitoring, logging – Splunk/Dynatrace), Performance optimization (parallel processing, large datasets), Data security basics (encryption, masking), API integration & data services exposure
What You'll Do.
Key contributor in datalake journey
Transitioning Payment Hub data from OLTP to datalake
Using datalake data for analytics and AI/ML initiatives
Work in a dedicated product development SCRUM team
Iterative delivery model
Design and build the Apache Spark/PySpark ETL pipeline (Bronze → Silver → Gold medallion architecture)
Implement Apache Iceberg table operations (MERGE
Design and validate the analytical star schema (fact/dimension tables
conformed dimensions)
Define and execute three-tier data quality rules
Build business logic connectors
transformation helpers
and custom derivations
Collaborate with stakeholders to clarify KPIs
and analytical use cases
Write comprehensive unit
How You'll Work.
Team & Collaboration
Work in a dedicated product development SCRUM team; Collaborate with stakeholders to clarify KPIs, query patterns, and analytical use cases; Excellent communication and collaboration skills
Communication Scope
Excellent communication and collaboration skills
Process & Methodology
SCRUM team, Iterative delivery model
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