Junior ETL And Apache Nifi Data Pipeline Engineer

What role will you play in the team

As a Junior ETL and Apache Nifi Data Pipeline Engineer stationed in Ahmedabad, you will be an integral pillar of our enterprise data integration and analytics infrastructure team. Your core mandate will involve designing, developing, and maintaining high-throughput data pipelines that ingest, transform, and load massive volumes of heterogeneous data into centralized data warehouses. You will bridge the gap between raw data sources and actionable analytics by ensuring seamless, secure, and fault-tolerant data flows across the entire enterprise ecosystem.

What you will do

You will actively design and configure complex data integration workflows using enterprise ETL tools, specifically focusing on Apache Nifi and Talend. Your daily tasks will include writing optimized SQL queries, establishing database connections with PostgreSQL and MySQL, building custom processors, and monitoring real-time data flow performance. You will troubleshoot pipeline failures, optimize transformation latency, ensure data governance standards are strictly met, and collaborate with data scientists to deliver clean, structured data for downstream machine learning initiatives.

Key responsibility

• Design, build, and orchestrate real-time and batch data pipelines using Apache Nifi, Talend, and enterprise ETL tools.
• Extract, transform, and load (ETL) data from diverse sources including relational databases, APIs, flat files, and cloud storage repositories.
• Write complex, highly optimized SQL queries, stored procedures, and triggers for PostgreSQL and MySQL database management systems.
• Implement robust error handling, exception logging, and alerting mechanisms within Apache Nifi data flow processors.
• Monitor pipeline execution performance, identify bottlenecks, and optimize data transformation speeds to handle growing volume requirements.
• Ensure data quality, integrity, and consistency by implementing rigorous validation rules and schema enforcement checks at ingestion points.
• Collaborate closely with data analysts and machine learning engineers to understand their downstream data consumption requirements and schema needs.

Required Qualification and Skills

Bachelor's degree in Information Technology, Computer Science, Electronics, or equivalent technical discipline.
• 0 to 1 year of practical experience in data engineering, ETL development, or database management environments.
• Hands-on proficiency with enterprise ETL tools, specifically Apache Nifi, Talend, or Informatica.
• Strong foundational expertise in SQL and working experience with database management systems like PostgreSQL, MySQL, or MongoDB.
• Basic programming capabilities in Python or Java for writing custom data transformation scripts and API integrations.
• Understanding of data warehousing concepts, dimensional modeling, star schemas, and snowflake schemas.
• Exceptional analytical aptitude, meticulous attention to detail, and strong organizational skills for managing multiple data workflows.

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Benefits Included

• Attractive starting salary package with annual performance-based appraisal reviews.
• Comprehensive health and accidental insurance coverage for peace of mind.
• Structured mentorship program pairing you with senior data infrastructure architects.
• Ample paid time off, casual leaves, and maternity/paternity leave policies.
• Sponsored professional certifications in cloud data engineering and ETL tools.
• Modern office workspace equipped with ergonomic seating, recreational areas, and subsidized catering.

A Day in the Life

Your workday kicks off by reviewing automated monitoring dashboards to verify the successful overnight execution of all critical data pipelines. Following the daily stand-up, you dive into Apache Nifi to design a new data routing flow for an incoming client CRM feed. You spend a couple of hours debugging an SQL performance issue in a PostgreSQL staging table, optimizing query execution plans. Post-lunch, you collaborate with the data science team to test a new data ingestion schema, ensuring all incoming features map correctly to their predictive modeling requirements.