REGISTRIEREN

Jobbörse

Finde Jobs in deiner Nähe – ob vor Ort, hybrid oder remote.
  • Ähnliche Jobs zu: Data Analyst, Patient Financial Services
XX
Data Engineer (Financial Services)10xTalents • Newark, New Jersey, United States
Jetzt Bewerben
XX

Data Engineer (Financial Services)

10xTalents
  • US
    Newark, New Jersey, United States
  • US
    Newark, New Jersey, United States
Jetzt Bewerben

Über

About the job Data Engineer (Financial Services)
Full-time, direct employment
Hybrid onsite/remote - Newark, NJ
No visa sponsorship or C2C at this time
Job Description:
Our client is seeking a skilled and experienced Data Engineer with expertise in Fixed Income Capital Markets to join their dynamic team. The ideal candidate will possess a strong technical background in data engineering, with specific experience in containerization, Python API development, streaming/messaging systems, and capital markets within Fixed Income.
Responsibilities:
Containerization Expertise:
Demonstrated proficiency in working with containerization technologies like ECS (Amazon Elastic Container Service) or Docker. Experience in deploying, managing, and scaling containerized applications in a production environment is essential.
Python API Development:
Extensive experience in developing APIs using Python, with a focus on building scalable and efficient data pipelines. Knowledge of Snowflake Snowpark coding is highly desirable, including the ability to leverage Snowpark for data processing tasks.
Streaming and Messaging Systems:
Strong understanding and practical experience with streaming platforms such as Kafka or Kinesis. Ability to design, implement, and optimize data streaming pipelines for real‑time data processing and analysis.
Fixed Income Capital Markets:
In-depth understanding of capital markets within Fixed Income, including bond markets, interest rates, credit products, and related financial instruments. Experience working with financial data and analytics in a Fixed Income context is highly preferred.
Data Engineering:
Collaborate with cross‑functional teams to design, build, and maintain data pipelines, ETL processes, and data warehouses. Ensure data quality, reliability, and scalability across various data sources and systems.
Problem Solving and Innovation:
Proactively identify opportunities for process improvement, automation, and optimization within the data engineering infrastructure. Drive innovation by implementing best practices and emerging technologies in data engineering.
Communication and Collaboration:
Work closely with data scientists, analysts, software engineers, and business stakeholders to understand requirements, gather feedback, and deliver impactful data solutions. Excellent communication skills are essential for effectively conveying technical concepts to non‑technical audiences.
Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, Finance, or related field.
Strong programming skills in Python, with experience in API development and data manipulation.
Hands‑on experience with containerization technologies like ECS or Docker.
Familiarity with Snowflake Snowpark for data processing tasks is a plus.
Proficiency in streaming/messaging systems such as Kafka or Kinesis.
Solid understanding of capital markets, particularly within Fixed Income.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and related services is advantageous.
Strong problem‑solving skills, attention to detail, and a passion for continuous learning and improvement.
This is an exciting opportunity for a Data Engineer who thrives in a fast‑paced environment and is passionate about leveraging cutting‑edge technologies to drive innovation in Fixed Income Capital Markets. If you have the required skills and experience, we invite you to apply for immediate consideration.
#J-18808-Ljbffr
  • Newark, New Jersey, United States

Sprachkenntnisse

  • English
Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.