Data Engineer Informatica, Cloudera & Spark

Job Description – Data Engineer (Informatica, Cloudera & Spark)

Position Details

Role: Data Engineer – Informatica, Cloudera & Spark

Job Type : Contract 2 hire

Location: Pune / Nagpur

Experience: 5+ Years

Work Mode: Work From Office

About the Role

We are seeking a skilled Data Engineer with strong expertise in Informatica, Cloudera, and Apache Spark to join our Data Engineering team. The ideal candidate will have hands-on experience in ETL development, big data technologies, and enterprise-scale data processing pipelines. This role involves designing, developing, optimizing, and supporting robust data integration solutions across on-premises and cloud-based environments.

Key Responsibilities

• Design, develop, and maintain ETL pipelines using Informatica.
• Build and support data processing workflows within the Cloudera/Hadoop ecosystem.
• Develop, optimize, and troubleshoot Apache Spark/PySpark applications.
• Perform data extraction, transformation, and loading (ETL/ELT) from multiple data sources.
• Write efficient SQL queries for data transformation, validation, and reporting.
• Monitor production ETL and Spark jobs, ensuring reliability and performance.
• Identify, analyze, and resolve data quality, performance, and pipeline-related issues.
• Support batch data processing and enterprise data integration workflows.
• Collaborate with business and technical stakeholders to understand requirements and deliver scalable solutions.
• Conduct unit testing, debugging, deployment, and production support activities.
• Create and maintain technical documentation for data pipelines, processes, and workflows.
• Follow data engineering best practices, coding standards, and governance guidelines.

Required Skills & Experience

• 5+ years of experience in Data Engineering, ETL Development, or related roles.
• Strong hands-on experience with Informatica (PowerCenter/BDM preferred).
• Experience working with Cloudera and Hadoop ecosystem components.
• Strong expertise in Apache Spark and PySpark development.
• Solid understanding of SQL and relational database concepts.
• Experience with ETL/ELT processes and data warehousing methodologies.
• Experience building and supporting enterprise-scale data pipelines.
• Strong analytical, troubleshooting, and debugging skills.
• Ability to work independently and collaborate effectively with cross-functional teams.

Preferred Qualifications

• Experience with Informatica PowerCenter, BDM, or Informatica Cloud (IICS).
• Exposure to Hadoop ecosystem tools such as Hive, HDFS, Kafka, and YARN.
• Experience working with cloud platforms such as AWS or Azure.
• Knowledge of data modeling and dimensional modeling concepts.
• Familiarity with CI/CD practices and version control tools such as Git.
• Experience in Banking, Financial Services, Insurance (BFSI), or other enterprise environments.

Key Skills

Informatica | Cloudera | Hadoop | Apache Spark | PySpark | SQL | ETL | ELT | Data Warehousing | Hive | Kafka | HDFS | Data Engineering

Candidate Profile

The ideal candidate is a hands-on Data Engineer with strong expertise in Informatica ETL development, Cloudera/Hadoop platforms, and Spark-based data processing. You should be capable of independently developing and supporting enterprise data pipelines, resolving complex technical issues, and contributing effectively to large-scale data engineering initiatives.