Senior Analyst - Data Engineering

LatentView; Bengaluru; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

LatentView in Bengaluru is seeking a Senior Analyst - Data Engineering with 3 to 5 years of hands-on experience in SQL, Python, PySpark and big data technologies. You will design, build, and test core data pipelines, data structures, and analytical engines within a modern data ecosystem.

You will develop and test ETL/ELT pipelines, contribute to data warehouse builds, and collaborate with cross-functional teams to translate business requirements into scalable data assets while ensuring data

Qualifications

• 3–5 years of experience in data engineering.
• Hands-on SQL, Python, PySpark and big data tech.
• Experience building ETL/ELT pipelines and data warehouses.
• Familiarity with data governance guidelines.

Responsibilities

• Develop, test, and maintain ETL/ELT pipelines and applications.
• Contribute to building data systems, databases, and data warehouses.
• Collaborate with stakeholders to translate business needs into data assets.
• Monitor performance, troubleshoot pipelines, and optimize SQL queries.
• Contribute to project delivery with strong analytical and communication skills.

Skills

SQL

Python

PySpark

Data Warehousing

Hadoop (HDFS/Hive)

ETL Pipelines

Tools

Airflow

Spark

Cloud Platforms

GenAI Tools

Job description

Designation : Senior Analyst - Data Engineering

Level : L2

Location : Bengaluru, Karnataka , India (BLR)

Experience : 3 to 5 Years

Job Role

We are looking for a Data Engineer with strong hands‑on expertise in SQL, Python, and big data technologies. In this role, you will work closely with senior team members and cross‑functional stakeholders to design, build, and test core data pipelines, database structures, and analytical engines. You will contribute directly to the day‑to‑day software development lifecycle in a modern big data ecosystem.

Responsibilities

• Development & Testing: Develop, unit test, and maintain efficient ETL/ELT pipelines and software applications using the clients technology stack.
• Data System Building: Contribute to the build‑out of data systems, databases, and data warehouses, ensuring compliance with data governance guidelines.
• Stakeholder Collaboration: Collaborate with cross‑functional stakeholders to understand immediate business requirements and turn them into scalable data assets.
• Support & Maintenance: Monitor performance, troubleshoot pipeline issues, optimize standard SQL queries, and ensure smooth data ingestion cycles.
• Problem Solving & Delivery: Actively contribute to overall project delivery, demonstrating strong analytical, communication, and collaborative team skills.

Required skills

• Primary Skills: Strong SQL, Python, PySpark, Data Warehousing Concepts, Hadoop Concepts (HDFS, Hive), ETL Data Pipelines.
• Secondary Skills: Airflow / Task Scheduling, Spark, Cloud Fundamentals (AWS / Azure / GCP), Exposure to AI/GenAI tools for code optimization.