Technical Risk Analyst

We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and data flows across modern cloud platforms including Azure, Databricks, Snowflake, and Kafka .

This role focuses on production-grade data engineering , enabling reliable ingestion, transformation, and delivery of data to analytics, risk, and machine-learning workloads. This position collaborates closely with analytics, fraud and DevOps teams, ensuring high data quality, availability, and performance ., Data Pipeline & Flow Development

• Design, build, and maintain batch and streaming data pipelines using Azure data services, Databricks (Spark), Snowflake, and Kafka .
• Develop end-to-end data flows from source systems through ingestion, transformation, and storage layers.
• Implement scalable ETL / ELT processes that support analytics, reporting, and machine learning use cases.

Cloud & Platform Engineering

• Build data solutions using cloud-native patterns (data lakes, lakehouse, data warehouses).
• Integrate data from relational, semi-structured, and streaming sources .
• Optimize pipeline performance, cost efficiency, and reliability in cloud environments.

Streaming & Event-Driven Data

• Develop and maintain real-time and near-real-time pipelines using Kafka or equivalent streaming technologies .
• Handle schema evolution, late-arriving data, and fault tolerance in streaming systems.

Data Quality & Reliability

• Implement data validation, monitoring, and alerting to ensure data accuracy and completeness.
• Troubleshoot pipeline failures and performance issues in production environments.
• Partner with analytics and downstream consumers to resolve data issues efficiently. [microsoft.ai] (https://microsoft.ai/job/mts-data-engineering/)

Collaboration & Delivery

• Work closely with data analysts, data scientists, and software engineers to understand data requirements.
• Participate in design reviews and contribute to data architecture discussions.
• Document data flows, schemas, and operational processes to support long-term maintainability.

• 2+ years of experience in data engineering, data management, or a related role.
• Hands-on experience building data pipelines using SQL and Python .
• Experience working with cloud data platforms (Azure preferred).
• Familiarity with Databricks / Apache Spark for data processing.
• Experience with data warehouses such as Snowflake .
• Basic experience or exposure to Kafka or streaming data pipelines .
• Strong understanding of ETL/ELT concepts, data modeling, and data lifecycle management .

Preferred Qualifications

• Experience with CI/CD for data pipelines and version control (Git, Azure DevOps, or similar).
• Exposure to lakehouse architectures and columnar formats (Parquet).
• Familiarity with data governance, metadata management, and access controls .
• Experience supporting analytics, BI, or machine-learning workloads .
• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved. If you want to make an impact on a global scale, come make a difference at Fiserv.