Senior Data Engineer

Fusionpact Technologies Inc; New York (NY); On-site; USD 140,000; Full time

Job summary

Fusionpact Technologies Inc is seeking a Senior Data Engineer to design and build high-performance data pipelines primarily for time series data. This role requires extensive experience in data engineering, particularly with tools like KDB+ and cloud technologies. The position demands collaboration within teams to ensure data availability and quality for machine learning processes, making it ideal for seasoned professionals in the field.

Qualifications

• 8+ years of experience in data engineering with focus on large-scale systems.
• Deep experience with time series data and storage systems.
• Strong experience with streaming and batch data pipelines.

Responsibilities

• Design, build, and optimize data pipelines for time series data.
• Implement scalable data infrastructure.
• Collaborate with data scientists to ensure data quality.

Skills

Data Engineering

Time Series Data

Data Pipelines

Python

Cloud Technologies

Tools

KDB+

TimeSet

Kronos

Glue

Kafka

Flink

Spark

Job description

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Domain: Information Technology (IT)

Location: USA - New York City, NY | Salt Lake City, UT | Dallas, TX

Salary: USD $140,000

Job Positions: 2

Experience: 8 – 15 Years

Work Authorization: US Citizens / Green Card Holders only

Work Mode: Onsite – 5 days a week

Shift Timing: 8:00 AM – 5:00 PM (General Shift)

What You’ll Do

• Design, build, and optimize high-performance data pipelines for large-scale time series data
• Implement scalable data infrastructure using tools such as KDB+, TimeSet (Google’s large time series database), or Kronos
• Develop efficient data ingestion and transformation workflows that handle real-time and historical time series data
• Connect time series data systems with Python-based model pipelines to support machine learning training and inference
• Collaborate with data scientists and ML engineers to ensure data availability, quality, and accessibility for experimentation and production
• Design data models and schemas optimized for time series use cases, including downsampling, aggregation, and indexing strategies
• Ensure system reliability, scalability, and performance through monitoring, testing, and tuning
• Establish data governance, lineage, and observability best practices in large-scale environments
• Mentor junior engineers on large-scale data design, distributed processing, and real-time system architecture
• Partner with product, engineering, and infrastructure teams to align data systems with business goals
  
  

Requirements

• 8+ years of experience in data engineering, with a focus on large-scale and high-throughput systems
• Deep experience working with time series data and purpose-built storage systems (e.g., KDB+, TimeSet, Kronos)
• Strong experience building streaming and batch data pipelines using tools like Glue, Kafka, Flink, or Spark
• Proficiency in Python and integrating data pipelines with machine learning workflows and libraries (e.g., pandas, NumPy, scikit-learn, PyTorch)
• Experience designing efficient, scalable data models and partitioning strategies for time series data
• Knowledge of distributed systems, columnar databases, and parallel processing
• Familiarity with cloud-native data architectures (AWS, GCP, or Azure) and containerized data infrastructure
• Strong understanding of data quality, lineage, monitoring, and observability tools
• Excellent communication skills and a proactive, consultative mindset in client-facing environments
  
  

Bonus

• Experience with multiple time series systems (e.g., KDB+ and Kronos)
• Contributing to open-source data infrastructure projects

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Industries

  Technology, Information and Media

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