Data
Engineer to build and manage data pipelines that support batch and
streaming data solutions. The role requires expertise in creating
seamless data flows across platforms like Data Lake/Lakehouse in
Cloudera, Azure Databricks, Kafka for both batch and stream data
pipelines etc.

Responsibilities

Strong
experience in develop, test, and maintain data pipelines (batch &
stream) using Cloudera, Spark, Kafka and Azure services like ADF,
Cosmos DB, Databricks, NoSQL DB/ Mongo DB etc.

Robust
programming skills in spark, python or scala & SQL.

Optimize
data pipelines to improve speed, performance, and reliability,
ensuring that data is available for data consumers as
required.

Create
ETL pipelines for downstream consumers by transform data as per
business logic.

Work
closely with Data Architects and Data Analysts to align data
solutions with business needs and ensure the accuracy and
accessibility of data.

Implement
data validation checks and error handling processes to maintain high
data quality and consistency across data pipelines.

Solid




analytical and problem solving skills, with a focus on optimizing
data flows and addressing impacts in the data pipeline.
Qualifications

8+
years of IT experience with at least 5+ years in data engineering and
cloud-based data platforms.

Strong
experience with Cloudera/any Data Lake, Confluent/Apache Kafka, and
Azure Data Services (ADF, Databricks, Cosmos DB).

Deep
knowledge of NoSQL databases (Cosmos DB, MongoDB) and data modeling
for performance and scalability.

Proven
expertise in designing and implementing batch and streaming data
pipelines using Databricks, Spark, or Kafka.

Experience
in creating scalable, reliable, and high-performance data solutions
with robust data governance policies.

Strong
collaboration skills to work with stakeholders, mentor junior Data
Engineers, and translate business needs into actionable
solutions.

Bachelors
or masters degree in computer science, IT, or a related field..

📌 Kafka Data Engineer (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India