Product integration analyst

Experience: 4 - 10 Years Location:P1: Bangalore (Hybrid), P2: Pune/Chennai Primary Skill: Apache NiFi as a mandatory, core skill PostgreSQL as the preferred SQL/database Education: BE/B.Tech/ M.Tech/MCA Full time. Role Overview We are looking for a Data Engineer / Data Specialist with strong expertise in Apache NiFi to design, build, and manage scalable data pipelines. This role is critical to our data infrastructure and involves developing robust data ingestion, processing, and storage solutions that support enterprise and edge services platforms.

Key Responsibilities Design and build scalable data pipelines using Apache NiFi to ingest data from multiple sources into data lakes and data warehouses. Develop, configure, and manage NiFi flows for both real-time and batch processing, ensuring data quality, reliability, and security. Collaborate with data scientists, analysts, and application teams to understand data requirements and deliver clean, well-structured datasets.

Optimize data pipelines for performance, scalability, and cost efficiency . Monitor, maintain, and troubleshoot data infrastructure to ensure high availability and stability. Implement data governance, security, and compliance policies.

Stay current with emerging data technologies and assess their applicability to the platform. Mandatory Skills 4–8 years of experience in data engineering with a strong focus on data pipelines. Hands-on expertise in Apache NiFi , including flow design, processor configuration, and performance tuning.

Proficiency in Python or Java . Strong SQL skills, preferably PostgreSQL . Experience with at least one cloud platform (preferably Google Cloud Platform ).

Understanding of data warehousing concepts and ETL / ELT methodologies . Familiarity with big data technologies such as Trino, Iceberg, DuckDB/Parquet, and Kafka . Additional Skills (Good to Have) Hands-on experience in Linux environments .

Experience with Docker and/or Kubernetes . Knowledge of monitoring, logging, and operational best practices for data pipelines. Responsibilities around: NiFi-based data ingestion and processing Building and managing data pipelines Data lake / data warehouse ingestion Performance tuning, monitoring, and governance