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Leads data engineering initiatives involving ETL/ELT pipelines, database optimization, orchestration, big data technologies, data modeling, BI performance, and data quality monitoring. Requires strong Scala, Python, SQL, and shell scripting skills, plus payments-domain expertise covering transaction processing, settlements, disputes, reconciliation, gateways, acquiring, issuing, and PCI-DSS compliance. The role also involves cross-functional communication, planning, facilitation, negotiation, and collaboration with senior stakeholders and clients.
- 7–9 years of hands-on experience in data engineering, preferably in the payments/financial services domain.
- Extensive experience with ETL/ELT frameworks and data pipeline tools.
- Strong programming skills in Scala, Python, SQL; experience with Java is a plus & shell scripting is mandatory.
- Strong SQL and database optimization skills; experience with NoSQL is a plus.
- Familiarity with orchestration tools such as Airflow, Prefect, Luigi, or similar.
- Experience working with big data technologies (Hadoop/Spark) preferred.
- Knowledge of data modelling (star/snowflake schemas), dimensional design, and BI performance optimization.
- Understanding of data quality frameworks, metrics, test automation tools, and monitoring.
Domain Knowledge
- Strong understanding of payments processing, transaction lifecycle, settlements, authorizations, disputes/refunds, and reconciliation flows.
- Experience with payment gateways, merchant acquiring, issuing, and banking interfaces is a plus.
- Familiarity with compliance and security standards relevant to payments (e.g., PCI-DSS).
- A bachelor’s or master’s degree in computer science, Engineering, or a related discipline.
- Ability to communicate effectively across multiple audiences, including firm-wide business units, senior leaders, associates and clients.
- Exceptional interpersonal skills, including teamwork, facilitation, and negotiation.
- Strong planning and organizational skills
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