Lead- Data Engineer

Actively Reviewing the Applications

Chapter247 Infotech

India, Madhya Pradesh, Indore Full-Time On-site INR 15–25 LPA

Posted 4 weeks ago • Apply by June 10, 2026

Job Description

Key Responsibilities

Extract and process data from multiple databases, APIs, and cloud platforms by establishing

strong source connections.

Design, develop, and maintain ETL pipelines for efficient data transformation and ingestion.
Write and optimize complex SQL queries for data extraction,validation,andreporting.
Utilize PySpark and BigData technologies(Hadoop,Spark,Databricks,etc.)to process and

analyze large datasets.

Perform data analysis using Python (Pandas,NumPy,etc.)to uncover trends,patterns,and insights.
Develop and maintain interactive dashboards and reports in Power BI(good to have).
Work with cross-functionalteams to understand business requirements and translate them into

data-driven solutions.

actionable manner.

Required Skills & Qualifications

Minimum 5+ Years of experience in data analytics, data engineering, or business intelligence.
Strong expertise in SQL(writing, optimizing, and managing complex queries).
Hands-on experience in ETL processes and building/maintaining data pipelines.
Experience working with Big Data technologies (Hadoop,Spark,PySpark,Databricks,etc.).
Proficiency in Python for data analysis(Pandas, NumPy, etc.).
Experience of working on Fabric
Experience of working on Databrick
Experience in connecting to and processing data from multiple data sources (databases, APIs, cloud platforms).
Experience of working on Cloud platforms ( Azure /AWS / GCP)
Experience of delivering the Projects
Experience of requirement understanding
Experience of preparing estimations and creating POCs
Experience of working with different Project domains.
Proficiency in delivering High –quality codes to clients
Proficiency in Data warehouse schema creation.
Experience of client communication.
Strong analytical and problem-solving skills.
Experience of mentoring and managing the team

Skills:- ADF, databricks, Microsoft Fabric, Azure, SQL and PySpark