Data Engineer

Eniac Systems; Hyderabad; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Eniac Systems in Hyderabad is seeking an expert data engineer to design and optimize data pipelines using Azure, Databricks, and Kafka. You will own batch and streaming ingestion while collaborating with cross-functional teams and mentoring junior engineers.

The role requires 7+ years in data engineering, strong SQL and PySpark/Scala, and hands-on experience with data lake architectures and Informatica tools. Join a fast-paced environment delivering scalable data platforms.

Qualifications

• 7+ years of experience in data engineering
• Strong experience with Azure Data Lake, Databricks, ADF
• Hands-on SQL and PySpark or Scala
• Proven experience with batch & real-time ingestion
• Experience with Kafka and big data processing
• Experience with Informatica PowerCenter
• Informatica IDMC or equivalent cloud data integration tools
• SQL Server, Oracle, Azure SQL
• Cosmos DB
• Unix/Linux
• Maestro (or similar enterprise schedulers)
• Data tools such as Precisely or equivalent

Responsibilities

• Design and build batch and streaming data pipelines using Azure, Databricks, and Kafka
• Develop ETL/ELT solutions using SQL, PySpark, or Scala
• Implement and support Data Lake / Lakehouse architectures
• Integrate data from legacy and modern platforms
• Apply data quality checks and support data governance basics (metadata, lineage, access controls)
• Optimize Spark jobs for performance, reliability, and cost
• Collaborate with cross-functional teams and mentor junior engineers

Skills

Azure Data Factory

Azure Data Lake

Databricks

Kafka

SQL

PySpark

Scala

Batch & real-time ingestion

Informatica PowerCenter

Informatica IDMC

Azure SQL

SQL Server

Oracle

Cosmos DB

Unix/Linux

Maestro

Precisely

Tools

Informatica PowerCenter

Informatica IDMC

Maestro

Precisely

Job description

location: Hyderabad

Skills: Azure Data Factory

Experience Required: 4-6

Key Responsibilities

• Design and build batch and streaming data pipelines using Azure, Databricks, and Kafka
• Develop ETL/ELT solutions using SQL, PySpark, or Scala
• Implement and support Data Lake / Lakehouse architectures
• Integrate data from legacy and modern platforms
• Apply data quality checks and support data governance basics (metadata, lineage, access controls)
• Optimize Spark jobs for performance, reliability, and cost
• Collaborate with cross-functional teams and mentor junior engineers

Required Skills & Experience

• 7+ years of experience in data engineering
• Strong experience with Azure Data Lake, Databricks, ADF
• Hands-on expertise in SQL and PySpark or Scala
• Proven experience with batch & real-time ingestion
• Experience with Kafka and big data processing
• Experience with:
• Informatica PowerCenter
• Informatica IDMC or equivalent cloud data integration tools
• SQL Server, Oracle, Azure SQL
• Cosmos DB
• Unix/Linux
• Maestro (or similar enterprise schedulers)
• Data tools such as Precisely or equivalent

Added Advantage

• Insurance domain knowledge (Policy, Claims, Billing, Underwriting, Actuarial, Regulatory data)
• Experience with Azure DevOps (AzDO) and GitHub-based CI/CD
• Practical usage of Copilot for data engineering and development productivity
• Exposure to Generative AI / GenAI use cases in data platforms and analytics