Amtex Systems Inc is an information technology and talent solutions company offering talent and BI consulting to the companies in US for over 25 years.
Our solutions are designed to fill resource gaps, by providing the right candidates who deliver value to the organization. Our propensity to nurture and build strong relationships with our clients helps us better understand their business demands and gives us the ability to provide services that are on time and rise above the rest.
Job Title: Senior Data Engineer (FinTech)
Job Location: Princeton, NJ
Work Model: Hybrid Preferred (Remote is possible)
Job Type: Permanent / Direct Hire
Must-Have Skills:
- Experience with FinTech/Financial services clients
- Python
- AWS
- Advanced SQL
- ETL Design & Implementation
- Relational Databases (MySQL, PostgreSQL, and Snowflake, etc.)
- Linux/UNIX & Bash Shell Scripting
Position Summary
We are seeking a Senior Data Engineer to join our team in Princeton, NJ. In this role, you will lead the design, development, and implementation of robust ETL solutions, advanced data models, and scalable business intelligence systems. You will collaborate closely with Quantitative, Risk, and Business stakeholders to analyze requirements, build enterprise datasets, and deliver high-performance data analytics platforms that drive core business strategy.
While financial industry experience is strongly preferred, we are open to exceptional engineering candidates from non-financial backgrounds who bring rigorous technical expertise.
Main Responsibilities
- Requirements & Architecture: Gather technical and business requirements, defining concepts, information needs, and database models to build enterprise-grade analytics solutions.
- ETL & Data Pipelines: Hands-on development of ETL pipelines, internal/external data feeds, and reporting infrastructure.
- Analytics & Surveillance: Build surveillance patterns and deep analytics processing solutions against large-scale data stores.
- Data Modeling: Design and implement data models, reports, visualizations, and analytics frameworks to support dynamic business intelligence capabilities.
- Stakeholder Collaboration: Partner directly with Quantitative, Risk, and Business teams to develop enterprise datasets and client-facing data products.
- Production Support: Maintain and support critical production systems, including off-hours support when necessary.
Qualifications & Requirements:
- Education: Minimum of a Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s degree / M.B.A. preferred).
- Experience: 5+ years of hands-on experience building ETL pipelines, data processing systems, and large-scale data analytics solutions.
Core Technical Stack:
- Strong expertise in Python (and/or C++).
- Strong expertise in AWS cloud environments.
- Advanced SQL and performance tuning.
- Experience with relational databases (MySQL, PostgreSQL, Snowflake, etc.).
- Strong proficiency in Linux/UNIX and Bash shell scripting.
- Data Processing: Significant experience handling large volumes of structured and unstructured data from diverse sources; familiarity with markup languages (JSON, XML, YAML).
Preferred / Nice-to-Have Skills:
- Experience with NoSQL and Time Series (OneTick) databases.
- Familiarity with AI/ML technologies (LLM-based agents, AWS Bedrock, n8n workflow automation).
- Knowledge of market data protocols (FIX, exchange order books).
- Experience with Big Data frameworks (Spark, Kafka, Hadoop ecosystem).
- Prior mentorship or technical guidance provided to junior engineers.
- Background in the financial sector.
Never miss an opportunity! Create an alert based on the job you applied for.
