Job Description
Job Title : Data Software Engineer
Location : Chennai or Coimbatore (Hybrid)
(Candidates willing to relocate to Chennai / Coimbatore are also eligible to apply)
Employment Type : Full-Time Permanent with Client
Notice Period : Immediate to 30 Days
Experience : 5 to 12 Years
Role Overview :
As a Data Software Engineer, you will design and implement scalable big data systems, develop real-time processing solutions, and optimize data workflows across multiple platforms.
You will work with cloud-native services, contribute to solution architecture, and ensure efficient data delivery for enterprise applications.
The role offers an exciting opportunity to solve large-scale data engineering challenges while working in a collaborative, agile environment
If you have hands-on experience in Big Data technologies, cloud platforms, and distributed data systems, this is a great opportunity to join a high-growth, innovation-driven team.
Essential Skills (Non-Negotiable)
- Apache Spark
- Python programming
- Cloud experience in AWS or Azure or GCP
- Strong SQL skills including complex queries and stored procedures
Mandatory Skills :
5 to 12 years of experience in Big Data technologiesExpert-level knowledge in Apache SparkStrong hands-on coding experience in PythonExperience with distributed computing systemsProficiency in the Hadoop ecosystem including MapReduce, HDFS, and SqoopExperience in stream processing using Apache Storm or Spark StreamingHands-on experience with messaging systems like Kafka or RabbitMQProficient in querying tools like Hive or ImpalaExperience integrating data from RDBMS, ERP systems, and flat filesGood understanding of NoSQL databases like HBase, Cassandra, or MongoDBExperience building and maintaining ETL pipelinesProven expertise in performance tuning of Spark jobsExperience working with cloud data services on AWS, Azure, or GCPAbility to lead and mentor junior engineersExperience designing scalable and resilient Big Data solutionsExperience working in Agile teamsPreferred Skills :
Familiarity with DataOps and CI or CD practices for data pipelinesExperience with enterprise-level data platform architecture(ref : hirist.tech)