Data Platform Software Engineer

Posted 17 Hours Ago
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Kansas City, MO, USA
In-Office
Mid level
Fintech • Software
The Role
Design, build, and maintain a cloud-native private-cloud data platform. Develop batch and real-time ingestion and transformation pipelines (Java/Python) using Flink, Spark, Kafka, Trino, and Iceberg. Implement metadata, governance, CI/CD, automation, monitoring, and performance tuning while collaborating with cross-functional teams to ensure reliability, security, and compliance.
Summary Generated by Built In

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.

Job Description

Job Title: Data Platform Software Engineer 

Location: Kansas City, MO (Remote Eligible) 

Company Overview:   

SS&C is a global leader in investment and financial services software, serving over 18,000 organizations worldwide. Headquartered in Windsor, Connecticut, SS&C is dedicated to driving innovation and client satisfaction across the financial services and healthcare industries. 

Job Description:    

We are seeking a skilled Data Platform Software Engineer to join our Data Platform team in Kansas City, MO. In this role, you will design, code, implement, support, and optimize a cloud-native data stack that leverages best-in-class open-source tools. The ideal candidate will design, build, support, and maintain an opinionated, resilient, and scalable data platform in a private cloud environment—enabling data-driven decision-making, analytics, and machine learning, while providing out-of-the-box deep insights. This role blends data engineering, software development, and infrastructure management, leveraging languages and tools such as Java, Python, Apache Iceberg, Flink, Spark, Kafka, and Trino.

Core Responsibilities 

Data Pipelines 

  • Develop and maintain robust, fault-tolerant data ingestion and transformation pipelines using Java, Python, Apache Flink, Spark, and Trino. 

  • Define flexible and scalable data schemas using Apache Iceberg. 

  • Support both batch and real-time data processing, including integration with Apache Kafka. 

  • Ensure reliability, observability, and integrity of data pipelines. 

Metadata Management & Data Governance 

  • Support metadata management platforms such as DataHub for data cataloging, lineage, and governance use cases. 

  • Collaborate with data stakeholders to align metadata solutions with organizational needs. 

  • Enforce governance policies related to data quality, privacy, and compliance (e.g., GDPR, CCPA). 

  • Implement fine-grained access controls, encryption, and auditing with a focus on regulatory compliance and data traceability. 

Automation & CI/CD 

  • Automate data pipelines, workflows, deployment, and infrastructure provisioning and configuration using tools like ArgoCD, Apache Airflow, Ansible, Salt, and Kubernetes. 

  • Implement CI/CD pipelines, actions, and workflows on GitHub to deploy updates and enhancements.

Performance Optimization 

  • Optimize data storage and queries using Apache Iceberg, Flink, and Spark to ensure high performance and low-latency access. 

  • Identify and address performance bottlenecks; implement partitioning, caching, and indexing strategies. 

Monitoring and Alerting 

  • Monitor data platform health using tools such as Prometheus and Grafana dashboards. 

  • Configure real-time alerts to proactively detect and resolve pipeline failures or data issues. 

  • Troubleshoot and resolve platform outages and data incidents promptly. 

Collaboration 

  • Work with other development teams and engineers to understand data needs and deliver performant, scalable solutions. 

  • Collaborate with cross-functional teams (Cloud Engineering, Network, and DevOps/Solutions Engineering) to troubleshoot and resolve infrastructure issues. 

Qualifications 

Education 

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. 

Experience 

  • 3+ years of experience in software and data engineering, with a strong focus on cloud-based data platforms. 

Technical Skills 

  • Strong programming skills in Java or Python. 

  • Knowledge of Apache Iceberg, Flink, Spark, Kafka, and Trino. 

  • Familiar with metadata management platforms like DataHub or Apache Atlas. 

  • Familiar with cloud-native infrastructure tools such as Kubernetes, Ansible, Salt, etc. 

  • Familiar with CI/CD and DevOps operations.

Soft Skills 

  • Strong analytical and problem-solving skills. 

  • Effective communication and collaboration with cross-functional teams.



Unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.



SS&C Technologies offers a comprehensive total rewards package designed to support your wellbeing, growth, and future. Our benefits include medical, dental, and vision coverage; a 401(k) plan with company match; paid time off, holidays, and parental leave; and professional development reimbursement opportunity.



 


Applications will be accepted on an ongoing basis until the position is filled.



SS&C Technologies is an Equal Employment Opportunity employer and does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.

Skills Required

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or related field
  • 3+ years of experience in software and data engineering with cloud-based data platforms
  • Strong programming skills in Java or Python
  • Knowledge of Apache Iceberg, Flink, Spark, Kafka, and Trino
  • Familiarity with metadata management platforms (DataHub or Apache Atlas)
  • Familiarity with cloud-native infrastructure tools such as Kubernetes, Ansible, Salt
  • Experience with CI/CD and DevOps operations (GitHub Actions, ArgoCD, Airflow, automation)
  • Experience with monitoring and observability tools (Prometheus, Grafana)
  • Strong analytical, problem-solving, communication, and collaboration skills
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