Kerala Architect java Jobs – 84 Open Jobs Today

Lead I - Software Engineering - Data Engineer – Spark & Streaming (GCP)
UST —Thiruvananthapuram, Kerala
- Computer Science
- DevOps
- Java
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Lead I - Software Engineering - Data Engineer – Spark & Streaming (GCP)

UST -
Thiruvananthapuram, Kerala

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Job details

Qualifications

CI/CD
Performance tuning
Computer Science
Cassandra
Kubernetes
Big data
DevOps
Spark
NoSQL
Google Cloud Platform
MongoDB
Java
Master's degree
Databases
SQL
Docker
Bachelor's degree
Machine learning
Scala
Continuous integration
APIs
ETL
IT
Apache
Kafka
Redshift
Python
Information Technology

Full job description

Role description

Data Engineer – Spark & Streaming (GCP)

Job Summary

The Data Engineer – Spark & Streaming is responsible for designing, developing, and maintaining scalable batch and real-time data pipelines using Apache Spark, Kafka, and Google Cloud Platform (GCP). The role focuses on building high-performance data platforms, optimizing data processing, and delivering reliable data solutions for analytics, reporting, and machine learning workloads.

Key Responsibilities

Design, develop, and maintain ETL/ELT pipelines for batch and real-time data processing.
Build scalable data pipelines using Apache Spark (PySpark/Scala) and streaming technologies such as Kafka and Flink.
Develop and optimize cloud-native data architectures on Google Cloud Platform (GCP).
Build and manage data lakes, data warehouses (BigQuery), and streaming platforms.
Optimize Spark jobs, SQL queries, and data processing workflows for performance and cost efficiency.
Implement data quality checks, monitoring, validation, and error-handling mechanisms.
Integrate data from multiple sources including databases, APIs, messaging systems, and cloud storage.
Collaborate with data architects, data scientists, and business stakeholders to deliver scalable data solutions.
Support CI/CD, deployment automation, and production troubleshooting.
Ensure data security, governance, and compliance with enterprise standards.

Must Have Skills

Minimum 8 years of IT experience.
Minimum 4+ years of recent hands-on experience with Google Cloud Platform (GCP).
Strong programming skills in Python and SQL.
Experience with Scala and/or Java is preferred.
Strong expertise in Apache Spark (Spark SQL, DataFrames, PySpark, Spark Streaming).
Hands-on experience with Apache Kafka, Google Pub/Sub, or other streaming technologies.
Experience designing and developing real-time streaming data pipelines.
Strong knowledge of BigQuery and GCP data services.
Experience with ETL/ELT frameworks and large-scale data processing.
Strong performance tuning skills for Spark jobs and SQL queries.
Experience implementing data quality, monitoring, and validation frameworks.
Excellent analytical, troubleshooting, and problem-solving skills.

Good to Have Skills

Experience with Apache Flink.
Knowledge of Snowflake, Amazon Redshift, or other cloud data warehouses.
Experience with NoSQL databases such as MongoDB, Cassandra, or Bigtable.
Hands-on experience with Apache Airflow for workflow orchestration.
Experience with Databricks.
Knowledge of Docker and Kubernetes.
Experience with CI/CD pipelines and DevOps practices.
Familiarity with machine learning data pipelines and feature engineering.
Google Cloud Professional Data Engineer certification is an added advantage.
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or equivalent experience.

Skills

big data,spark,bigquery,sql,apache kafka,scala,

About UST
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients’ organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact—touching billions of lives in the process.

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