Data Engineer (Flink & Iceberg)

Navikenz; Bengaluru; On-site; INR 900,000 - 1,600,000; Full time

Job summary

A leading technology firm in Bengaluru is looking for an experienced Data Engineer to build and maintain scalable data pipelines for a next-generation data platform. Collaborating closely with AI/ML engineers and data scientists, you will design real-time and batch pipelines while ensuring data quality and observability. Ideal candidates have over 4 years of experience in data engineering, proficient in Python and SQL, and familiar with tools like Kafka and Airflow. Join us to contribute to innovative data solutions.

Qualifications

• 4+ years in data engineering roles, with at least 2 years handling real-time or streaming pipelines.
• Experience with hybrid/on-prem and cloud platforms (AWS/GCP/Azure) deployments.
• Knowledge of DevOps practices, Docker/Kubernetes, Terraform or Ansible.

Responsibilities

• Design and implement real-time and batch pipelines for high-throughput data ingestion.
• Develop data models and manage data lakes and warehouses for analytical workloads.
• Ensure pipeline scalability, observability, and data quality through monitoring and validation.

Skills

Python

SQL

Apache Kafka

Apache Spark

Data Modeling

Airflow

Terraform

Data Lakes/Warehouses

Docker/Kubernetes

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

Apache Flink

AWS

GCP

Azure

Job description

We are seeking an experienced Data Engineer to build and maintain scalable, high-performance data pipelines and infrastructure for our next-generation data platform. The platform ingests and processes real-time and historical data from diverse industrial sources such as airport systems, sensors, cameras, and APIs. You will work closely with AI/ML engineers, data scientists, and DevOps to enable reliable analytics, forecasting, and anomaly detection use cases.

Key Responsibilities

• Design and implement real-time (Kafka,Spark/Flink)and batch (Airflow,Spark)pipelines for high-throughput data ingestion, processing, and transformation.
• Develop data models and manage data lakes and warehouses (Delta Lake,Iceberg,etc) to support both analytical and ML workloads.
• Integrate data from diverse sources: IoT sensors, databases (SQL/NoSQL), REST APIs, and flat files.
• Ensure pipeline scalability, observability, and data quality through monitoring, alerting, validation, and lineage tracking.
• Collaborate with AI/ML teams to provision clean and ML-ready datasets for training and inference.
• Deploy, optimize, and manage pipelines and data infrastructure across on-premise and hybrid environments.
• Participate in architectural decisions to ensure resilient, cost-effective, and secure data flows.
• Contribute to infrastructure-as-code and automation for data deployment using Terraform, Ansible, or similar tools.

Qualifications & Required Skills

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• 4+ years in data engineering roles, with at least 2 years handling real-time or streaming pipelines.
• Strong programming skills in Python/Javaand SQL.
• Experience with Apache Kafka, Apache Spark, or Apache Flink for real-time and batch processing.
• Hands‑on with Airflow, dbt, or other orchestration tools.
• Familiarity with data modeling (OLAP/OLTP), schema evolution, and format handling (Parquet, Avro, ORC).
• Experience with hybrid/on-prem and cloud platforms (AWS/GCP/Azure) deployments.
• Proficient in working with data lakes/warehouses like Snowflake, BigQuery, Redshift, or Delta Lake.
• Knowledge of DevOps practices, Docker/Kubernetes, Terraform or Ansible.
• Exposure to data observability, data cataloging, and quality tools (e.g., Great Expectations, OpenMetadata).

Good-to-Have

• Experience with time-series databases (e.g., InfluxDB, TimescaleDB) and sensor data.
• Prior experience in domains such as aviation, manufacturing, or logistics is a plus.