Sr. Data Engineer

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

Sr. Data Engineer

Locations: San Francisco, CA / Jacksonville, FL / Boston, MA / New York, NY (Hybrid)

Get To Know The Team:

Our mission and team are expanding, and we are looking for motivated people who want to be part of an exciting growth opportunity in the Fintech industry.

Why You Will Love It Here!

• Flexibility: Hybrid Work Model & a Business Casual Dress Code, including jeans
• Your Future: 401k Matching Program, Professional Development Reimbursement
• Work/Life Balance: Flexible Personal/Vacation Time Off, Sick Leave, Paid Holidays
• Your Wellbeing: Medical, Dental, Vision, Employee Assistance Program, Parental Leave
• Wide Ranging Perspectives: Committed to Celebrating the Variety of Backgrounds, Talents, and Experiences of Our Employees
• Training: Hands-On, Team-Customized, including SS&C University
• Extra Perks: Discounts on fitness clubs, travel and more!

What You Will Get To Do:

• Join a team that creates a leading cloud platform with the latest big data, cloud-native and machine learning technologies
• Build and implement models in a production environment for a revenue-driving product.
• Create and maintain overall optimal data infrastructure.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Manage data migrations/conversions and troubleshoot data processing issues.
• Create the pipeline for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources.
• Build machine learning functions to help with data automation and data preparation.
• Work closely with our product team and data warehouse engineers to build analytics tools and dashboards that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Work with other data experts to strive for greater functionality in our data systems.
• Discover more innovative machine-learning solutions that can drive business values.

What You Will Bring:

• Passionate about big data and building a platform.
• Proficient coding skills and strong algorithm & data structure basis.
• Knowledge of one or multiple of the tools: Hadoop, Spark, Presto, Hive, Kafka, or Airflow.
• Skills in transforming data, developing data structures, building a metadata store, and setting up data pipelines or data workflows.
• Experience in getting data through API with Python or other programming languages such as JavaScript, Java, C#, Scala, etc
• Strong problem-solving skills with a can-do attitude.
• Great software engineering best practices with git and version control systems.
• Solid communication skills to explain complex data pipelines to both technical and non-technical people.
• Excellent writing and documenting skills.
• Self-starter and self-motivated.
• Bachelor’s Degree in Computer Science, Information Systems or other STEM field
• 5+ years of experience in data engineering or a related field required

Bonus if you have

• Machine learning academic or working experiences.
• Kubernetes or docker knowledge.
• Experience with AWS Glue, Azure Data Factory, or Data Bricks.

Thank you for your interest in SS&C! To further explore this opportunity, please apply through our careers page on the corporate website at www.ssctech.com/careers.

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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 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.