Senior Data Engineer

InRhythm; Bengaluru; On-site; INR 1,800,000 - 2,500,000; Full time

Benefits offered by this job

High-visibility data projects

Collaborative autonomous teams

Continuous learning opportunities

Job summary

A leading tech consultancy in Bengaluru is seeking a Senior Data Engineer to lead the design and implementation of large-scale time series data systems. The ideal candidate will have over 8 years of experience in data engineering, focusing on high-throughput systems and proficiency in tools such as KDB+ and Python. This role offers the opportunity to work on high-impact data projects, lead from within empowered teams, and grow through mentorship and shared knowledge.

Qualifications

• 8+ years of experience in data engineering focused on large-scale systems.
• Deep knowledge of time series data storage systems.
• Strong proficiency in Python and data pipeline integration.

Responsibilities

• Architect and implement large-scale time series data pipelines.
• Design data models optimized for time series use cases.
• Mentor junior engineers on data design and processing.

Skills

Large-scale data systems expertise

Python integration

Streaming and batch data pipelines

Real-time and historical data management

Data quality and monitoring tools

Tools

KDB+

TimeSet

Glue

Kafka

Spark

Job description

Senior Talent Acquisition and Recruitment | Connecting Next-Level Talent to Opportunities That Grow Their Careers

Build What Matters—Large-Scale Data Engineering Leadership

At InRhythm, we don’t just build apps—we transform industries. We launch high-impact digital platforms, modernize mission-critical systems, and create human-centered experiences that shape the way people live, work, and thrive.

We’re seeking a Senior Data Engineer with expertise in large-scale time series data systems to lead the design and implementation of robust, scalable, and efficient data infrastructure. This is a strategic and hands-on role for someone passionate about powering advanced analytics and model-driven decision-making through high-performance data engineering.

Who We Are

We’re InRhythm. We build high-impact digital products that solve real-world problems at scale.

Since 2002, we’ve helped modernize platforms and accelerate innovation for some of the world’s most recognized enterprises—including Goldman Sachs, Morgan Stanley, Mastercard, Fidelity, UnitedHealth Group, Amazon, and more.

We specialize in web, mobile, cloud-native, and data-intensive systems—but what sets us apart is our culture of craftsmanship, velocity, and outcome-driven delivery. We don’t wait to be told what to do. We lead from within.

Build the Data-Driven Future

Data isn’t just infrastructure—it’s intelligence in motion.

As a Senior Data Engineer, you’ll architect and implement large-scale time series data pipelines that support high-throughput ingestion, real-time querying, and seamless integration with Python-based machine learning workflows. You’ll work closely with engineering, analytics, and data science teams to ensure data systems are reliable, high-performance, and optimized for large volumes and low-latency workloads.

Your work will enable model training, evaluation, and inference on dynamic, continuously evolving datasets that drive real-time insight and innovation.

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) or contributing to open-source data infrastructure projects

Why You’ll Thrive at InRhythm

• Work on high-visibility, high-impact data projects that shape enterprise intelligence
• Collaborate with forward-thinking engineers, scientists, and product leaders
• Lead from within empowered, autonomous teams that value outcomes over process
• Grow through shared knowledge, mentorship, and continuous learning
• Influence how modern data infrastructure is built and scaled for the future

We don’t just build—we build what’s next. Together.